In [2]:
## Import Modules
from sklearn.feature_selection import RFECV
from sklearn.feature_selection import RFE
import statsmodels.api as sm
from sklearn.metrics import completeness_score, homogeneity_score
from sklearn.cluster import KMeans
from sklearn.model_selection import GridSearchCV
import math
from sklearn import feature_selection
import graphviz
from sklearn import metrics
from sklearn.tree import export_graphviz
from sklearn import cross_validation
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn import tree
import seaborn as sns
from sklearn import preprocessing
import numpy as np
import pandas as pd
import os
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline
3#from sklearn import tree, naive_bayes
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
C:\Users\lenovo\Anaconda2\lib\site-packages\sklearn\cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.
  "This module will be removed in 0.20.", DeprecationWarning)
In [3]:
##get working directory
os.getcwd()
Out[3]:
'C:\\Depaul_Win7\\DSC 478 Machine Learning\\Final Project\\health_adult'
In [4]:
os.chdir('C:\\Depaul_Win7\\DSC 478 Machine Learning\\Final Project\\health_adult')
In [5]:
##load data via read_csv
health_df = pd.read_csv('samadult.csv', sep=",")
health_df.head()
Out[5]:
FPX FMX HHX INTV_QRT WTIA_SA WTFA_SA SEX HISPAN_I R_MARITL MRACRPI2 ... MBO_PRO1 YTQU_YG1 YTQ_BTY1 YTQ_MDY1 YTQU_TA1 YTQ_BTT1 YTQ_MDT1 YTQU_QG1 YTQ_BTQ1 YTQ_MDQ1
0 1 1 3 1 5829.3 5044 2 12 4 1 ... 2 2 NaN NaN 2 NaN NaN 2 NaN NaN
1 1 1 9 1 2752.4 3770 1 12 7 1 ... 2 2 NaN NaN 2 NaN NaN 2 NaN NaN
2 2 1 11 1 14902.0 17305 1 12 1 1 ... 2 2 NaN NaN 2 NaN NaN 2 NaN NaN
3 1 1 15 1 8531.8 7383 2 12 5 1 ... 2 1 1.0 1.0 1 1.0 2.0 2 NaN NaN
4 1 1 18 1 5477.2 8314 1 0 1 1 ... 2 1 1.0 1.0 2 NaN NaN 2 NaN NaN

5 rows × 702 columns

In [6]:
#check types
health_df.dtypes
Out[6]:
FPX           int64
FMX           int64
HHX           int64
INTV_QRT      int64
WTIA_SA     float64
WTFA_SA       int64
SEX           int64
HISPAN_I      int64
R_MARITL      int64
MRACRPI2      int64
RACERPI2      int64
MRACBPI2      int64
AGE_P         int64
RECTYPE       int64
SRVY_YR       int64
INTV_MON      int64
REGION        int64
PSTRAT        int64
PPSU          int64
PROX1       float64
PROX2       float64
LATEINTA      int64
PROXYSA       int64
PAR_STAT      int64
FDRN_FLG      int64
DOINGLWA      int64
WHYNOWKA    float64
EVERWRK     float64
SUPERVIS    float64
WRKCATA     float64
             ...   
AWEBUSE       int64
AWEBOFNO    float64
AWEBOFTP    float64
AWEBEML       int64
AWEBMNO     float64
AWEBMTP     float64
NAT_USM1      int64
CHE_USM1      int64
TRD_USM1      int64
TR_USM21    float64
TR_USM22    float64
TR_USM23    float64
TR_USM24    float64
TR_USM25    float64
TR_USM26    float64
HOM_USM1      int64
MBO_MAN1      int64
MBO_MND1      int64
MBO_SPR1      int64
MBO_IMG1      int64
MBO_PRO1      int64
YTQU_YG1      int64
YTQ_BTY1    float64
YTQ_MDY1    float64
YTQU_TA1      int64
YTQ_BTT1    float64
YTQ_MDT1    float64
YTQU_QG1      int64
YTQ_BTQ1    float64
YTQ_MDQ1    float64
Length: 702, dtype: object
In [7]:
columnNames = list(health_df.head(0))
print(columnNames)
['FPX', 'FMX', 'HHX', 'INTV_QRT', 'WTIA_SA', 'WTFA_SA', 'SEX', 'HISPAN_I', 'R_MARITL', 'MRACRPI2', 'RACERPI2', 'MRACBPI2', 'AGE_P', 'RECTYPE', 'SRVY_YR', 'INTV_MON', 'REGION', 'PSTRAT', 'PPSU', 'PROX1', 'PROX2', 'LATEINTA', 'PROXYSA', 'PAR_STAT', 'FDRN_FLG', 'DOINGLWA', 'WHYNOWKA', 'EVERWRK', 'SUPERVIS', 'WRKCATA', 'BUSINC1A', 'LOCALL1B', 'WRKLONGH', 'HOURPDA', 'PDSICKA', 'ONEJOB', 'WRKLYR4', 'INDSTRN1', 'INDSTRN2', 'OCCUPN1', 'OCCUPN2', 'YRSWRKPA', 'DIFAGE2', 'HYPEV', 'HYPDIFV', 'HYBPCKNO', 'HYBPCKTP', 'HYBPLEV', 'HYPMDEV2', 'HYPMED2', 'CHLEV', 'CHLYR', 'CLCKNO', 'CLCKTP', 'CHLMDEV2', 'CHLMDNW2', 'CHDEV', 'ANGEV', 'MIEV', 'HRTEV', 'STREV', 'EPHEV', 'JAWP', 'WEA', 'CHE', 'ARM', 'BRTH', 'AHADO', 'FACE', 'SPEAKING', 'EYE', 'WALKING', 'HEADACHE', 'ASTDO', 'COPDEV', 'ASPMEDEV', 'ASPMEDAD', 'ASPMDMED', 'ASPONOWN', 'AASMEV', 'AASSTILL', 'AASMYR', 'AASERYR1', 'ULCEV', 'ULCYR', 'CANEV', 'CNKIND1', 'CNKIND2', 'CNKIND3', 'CNKIND4', 'CNKIND5', 'CNKIND6', 'CNKIND7', 'CNKIND8', 'CNKIND9', 'CNKIND10', 'CNKIND11', 'CNKIND12', 'CNKIND13', 'CNKIND14', 'CNKIND15', 'CNKIND16', 'CNKIND17', 'CNKIND18', 'CNKIND19', 'CNKIND20', 'CNKIND21', 'CNKIND22', 'CNKIND23', 'CNKIND24', 'CNKIND25', 'CNKIND26', 'CNKIND27', 'CNKIND28', 'CNKIND29', 'CNKIND30', 'CNKIND31', 'PREGEVER', 'DBHVPAY', 'DBHVCLY', 'DBHVWLY', 'DBHVPAN', 'DBHVCLN', 'DBHVWLN', 'DIBREL', 'DIBEV1', 'DIBPRE2', 'DIBTEST', 'DIBTYPE', 'DIBPILL1', 'INSLN1', 'DIBINS2', 'DIBINS3', 'DIBINS4', 'EPILEP1', 'EPILEP2', 'EPILEP3', 'EPILEP4', 'EPILEP5', 'DIBGDM', 'DIBBABY', 'DIBPRGM', 'DIBREFER', 'DIBBEGIN', 'AHAYFYR', 'SINYR', 'CBRCHYR', 'KIDWKYR', 'LIVYR', 'JNTSYMP', 'JMTHP1', 'JMTHP2', 'JMTHP3', 'JMTHP4', 'JMTHP5', 'JMTHP6', 'JMTHP7', 'JMTHP8', 'JMTHP9', 'JMTHP10', 'JMTHP11', 'JMTHP12', 'JMTHP13', 'JMTHP14', 'JMTHP15', 'JMTHP16', 'JMTHP17', 'JNTCHR', 'JNTHP', 'ARTH1', 'ARTHLMT', 'PAINECK', 'PAINLB', 'PAINLEG', 'PAINFACE', 'AMIGR', 'ACOLD2W', 'AINTIL2W', 'PREGNOW', 'PREGFLYR', 'HRAIDNOW', 'HRAIDEV', 'AHEARST1', 'AVISION', 'ABLIND', 'VIM_DREV', 'VIMLS_DR', 'VIM_CAEV', 'VIMLS_CA', 'VIMCSURG', 'VIM_GLEV', 'VIMLS_GL', 'VIM_MDEV', 'VIMLS_MD', 'VIMGLASS', 'VIMREAD', 'VIMDRIVE', 'AVISREH', 'AVISDEV', 'AVDF_NWS', 'AVDF_CLS', 'AVDF_NIT', 'AVDF_DRV', 'AVDF_PER', 'AVDF_CRD', 'AVISEXAM', 'AVISACT', 'AVISPROT', 'LUPPRT', 'CHPAIN6M', 'PAINLMT', 'HYPYR1', 'CANAGE1', 'CANAGE2', 'CANAGE3', 'CANAGE4', 'CANAGE5', 'CANAGE6', 'CANAGE7', 'CANAGE8', 'CANAGE9', 'CANAGE10', 'CANAGE11', 'CANAGE12', 'CANAGE13', 'CANAGE14', 'CANAGE15', 'CANAGE16', 'CANAGE17', 'CANAGE18', 'CANAGE19', 'CANAGE20', 'CANAGE21', 'CANAGE22', 'CANAGE23', 'CANAGE24', 'CANAGE25', 'CANAGE26', 'CANAGE27', 'CANAGE28', 'CANAGE29', 'CANAGE30', 'DIBAGE1', 'ACHRC14A', 'ADURA14A', 'ADURB14A', 'AFLHC19_', 'AFLHC20_', 'AFLHC21_', 'AFLHC22_', 'AFLHC23_', 'AFLHC24_', 'AFLHC25_', 'AFLHC26_', 'AFLHC27_', 'AFLHC28_', 'AFLHC29_', 'AFLHC30_', 'AFLHC31_', 'AFLHC32_', 'AFLHC33_', 'AFLHC34_', 'AFLHCA1', 'AFLHCA10', 'AFLHCA11', 'AFLHCA12', 'AFLHCA13', 'AFLHCA15', 'AFLHCA16', 'AFLHCA17', 'AFLHCA18', 'AFLHCA2', 'AFLHCA3', 'AFLHCA4', 'AFLHCA5', 'AFLHCA6', 'AFLHCA7', 'AFLHCA8', 'AFLHCA9', 'AFLHCA90', 'AFLHCA91', 'AHSTATYR', 'ALCHRC1', 'ALCHRC10', 'ALCHRC11', 'ALCHRC12', 'ALCHRC13', 'ALCHRC15', 'ALCHRC16', 'ALCHRC17', 'ALCHRC18', 'ALCHRC19', 'ALCHRC2', 'ALCHRC20', 'ALCHRC21', 'ALCHRC22', 'ALCHRC23', 'ALCHRC24', 'ALCHRC25', 'ALCHRC26', 'ALCHRC27', 'ALCHRC28', 'ALCHRC29', 'ALCHRC3', 'ALCHRC30', 'ALCHRC31', 'ALCHRC32', 'ALCHRC33', 'ALCHRC34', 'ALCHRC4', 'ALCHRC5', 'ALCHRC6', 'ALCHRC7', 'ALCHRC8', 'ALCHRC9', 'ALCHRC90', 'ALCHRC91', 'ALCHRONR', 'ALCNDRT', 'ALDURA1', 'ALDURA10', 'ALDURA11', 'ALDURA12', 'ALDURA13', 'ALDURA15', 'ALDURA16', 'ALDURA17', 'ALDURA18', 'ALDURA19', 'ALDURA2', 'ALDURA20', 'ALDURA21', 'ALDURA22', 'ALDURA23', 'ALDURA24', 'ALDURA25', 'ALDURA26', 'ALDURA27', 'ALDURA28', 'ALDURA29', 'ALDURA3', 'ALDURA30', 'ALDURA31', 'ALDURA32', 'ALDURA33', 'ALDURA34', 'ALDURA4', 'ALDURA5', 'ALDURA6', 'ALDURA7', 'ALDURA8', 'ALDURA9', 'ALDURA90', 'ALDURA91', 'ALDURB1', 'ALDURB10', 'ALDURB11', 'ALDURB12', 'ALDURB13', 'ALDURB15', 'ALDURB16', 'ALDURB17', 'ALDURB18', 'ALDURB19', 'ALDURB2', 'ALDURB20', 'ALDURB21', 'ALDURB22', 'ALDURB23', 'ALDURB24', 'ALDURB25', 'ALDURB26', 'ALDURB27', 'ALDURB28', 'ALDURB29', 'ALDURB3', 'ALDURB30', 'ALDURB31', 'ALDURB32', 'ALDURB33', 'ALDURB34', 'ALDURB4', 'ALDURB5', 'ALDURB6', 'ALDURB7', 'ALDURB8', 'ALDURB9', 'ALDURB90', 'ALDURB91', 'ALHCA14A', 'ALTIME1', 'ALTIME10', 'ALTIME11', 'ALTIME12', 'ALTIME13', 'ALTIME15', 'ALTIME16', 'ALTIME17', 'ALTIME18', 'ALTIME19', 'ALTIME2', 'ALTIME20', 'ALTIME21', 'ALTIME22', 'ALTIME23', 'ALTIME24', 'ALTIME25', 'ALTIME26', 'ALTIME27', 'ALTIME28', 'ALTIME29', 'ALTIME3', 'ALTIME30', 'ALTIME31', 'ALTIME32', 'ALTIME33', 'ALTIME34', 'ALTIME4', 'ALTIME5', 'ALTIME6', 'ALTIME7', 'ALTIME8', 'ALTIME9', 'ALTIME90', 'ALTIME91', 'ALUNIT1', 'ALUNIT10', 'ALUNIT11', 'ALUNIT12', 'ALUNIT13', 'ALUNIT15', 'ALUNIT16', 'ALUNIT17', 'ALUNIT18', 'ALUNIT19', 'ALUNIT2', 'ALUNIT20', 'ALUNIT21', 'ALUNIT22', 'ALUNIT23', 'ALUNIT24', 'ALUNIT25', 'ALUNIT26', 'ALUNIT27', 'ALUNIT28', 'ALUNIT29', 'ALUNIT3', 'ALUNIT30', 'ALUNIT31', 'ALUNIT32', 'ALUNIT33', 'ALUNIT34', 'ALUNIT4', 'ALUNIT5', 'ALUNIT6', 'ALUNIT7', 'ALUNIT8', 'ALUNIT9', 'ALUNIT90', 'ALUNIT91', 'ATIME14A', 'AUNIT14A', 'BEDDAYR', 'FLA1AR', 'FLCARRY', 'FLCLIMB', 'FLGRASP', 'FLPUSH', 'FLREACH', 'FLRELAX', 'FLSHOP', 'FLSIT', 'FLSOCL', 'FLSTAND', 'FLSTOOP', 'FLWALK', 'SPECEQ', 'WKDAYR', 'ALC12MNO', 'ALC12MTP', 'ALC1YR', 'ALC5UPN1', 'ALC5UPT1', 'ALC5UPY1', 'ALCAMT', 'ALCLIFE', 'BINGE1', 'CIG30D2', 'CIGAREV2', 'CIGCUR2', 'CIGDAMO', 'CIGQTYR', 'CIGSDA1', 'CIGSDA2', 'ECIG30D2', 'ECIGCUR2', 'ECIGEV2', 'MODLNGNO', 'MODLNGTP', 'MODNO', 'MODTP', 'PIPECUR2', 'PIPEV2', 'SMKEV', 'SMKLSCR2', 'SMKLSTB1', 'SMKNOW', 'SMKQTNO', 'SMKQTTP', 'SMKREG', 'STRNGNO', 'STRNGTP', 'VIGLNGNO', 'VIGLNGTP', 'VIGNO', 'VIGTP', 'SMKSTAT2', 'SMKQTY', 'CIGSDAY', 'VIGFREQW', 'MODFREQW', 'STRFREQW', 'VIGMIN', 'MODMIN', 'ALC12MWK', 'ALC12MYR', 'ALCSTAT', 'AHEIGHT', 'AWEIGHTP', 'BMI', 'AUSUALPL', 'APLKIND', 'AHCPLROU', 'AHCPLKND', 'AHCCHGYR', 'AHCCHGHI', 'APRVTRYR', 'APRVTRFD', 'ADRNANP', 'ADRNAI', 'AHCDLYR1', 'AHCDLYR2', 'AHCDLYR3', 'AHCDLYR4', 'AHCDLYR5', 'AHCAFYR1', 'AHCAFYR2', 'AHCAFYR3', 'AHCAFYR4', 'AHCAFYR5', 'AHCAFYR6', 'AWORPAY', 'AHICOMP', 'ARX12MO', 'ARX12_1', 'ARX12_2', 'ARX12_3', 'ARX12_4', 'ARX12_5', 'ARX12_6', 'ADNLONG2', 'AHCSYR1', 'AHCSYR2', 'AHCSYR3', 'AHCSYR4', 'AHCSYR5', 'AHCSYR6', 'AHCSYR7', 'AHCSYR8', 'AHCSYR9', 'AHCSYR10', 'AHERNOY2', 'AERVISND', 'AERHOS', 'AERREA1R', 'AERREA2R', 'AERREA3R', 'AERREA4R', 'AERREA5R', 'AERREA6R', 'AERREA7R', 'AERREA8R', 'AHCHYR', 'AHCHMOYR', 'AHCHNOY2', 'AHCNOYR2', 'ASRGYR', 'AMDLONGR', 'HIT1A', 'HIT2A', 'HIT3A', 'HIT4A', 'HIT5A', 'FLUVACYR', 'FLUVACTP', 'FLUVAC_M', 'FLUVAC_Y', 'FLUSHPG1', 'FLUSHPG2', 'SHTPNUYR', 'APOX', 'APOX12MO', 'AHEP', 'AHEPLIV', 'AHEPBTST', 'SHTHEPB', 'SHEPDOS', 'SHTHEPA', 'SHEPANUM', 'AHEPCTST', 'AHEPCRES', 'SHINGLES', 'SHTTD', 'SHTHPV2', 'SHHPVDOS', 'AHPVAGE', 'LIVEV', 'TRAVEL', 'WRKDIR', 'APSBPCHK', 'APSCHCHK', 'APSBSCHK', 'APSPAP', 'APSMAM', 'APSCOL', 'APSDIET', 'APSSMKC', 'AINDPRCH', 'AINDWHO', 'AINDDIF1', 'AINDDIF2', 'AEXCHNG', 'CLAS1', 'CLAS2', 'CLAS3', 'CLAS4', 'CLAS5', 'SHTTDAP2', 'WRKHLTH2', 'AINDINS2', 'ASRGNOYP', 'ASICPUSE', 'ASISATHC', 'ASITENUR', 'ASINHELP', 'ASINCNTO', 'ASINTRU', 'ASINKNT', 'ASISIM', 'ASISIF', 'ASIRETR', 'ASIMEDC', 'ASISTLV', 'ASICNHC', 'ASICCOLL', 'ASINBILL', 'ASIHCST', 'ASICCMP', 'ASISLEEP', 'ASISLPFL', 'ASISLPST', 'ASISLPMD', 'ASIREST', 'ASISAD', 'ASINERV', 'ASIRSTLS', 'ASIHOPLS', 'ASIEFFRT', 'ASIWTHLS', 'ASIMUCH', 'ASIHIVT', 'ASIHIVWN', 'AWEBUSE', 'AWEBOFNO', 'AWEBOFTP', 'AWEBEML', 'AWEBMNO', 'AWEBMTP', 'NAT_USM1', 'CHE_USM1', 'TRD_USM1', 'TR_USM21', 'TR_USM22', 'TR_USM23', 'TR_USM24', 'TR_USM25', 'TR_USM26', 'HOM_USM1', 'MBO_MAN1', 'MBO_MND1', 'MBO_SPR1', 'MBO_IMG1', 'MBO_PRO1', 'YTQU_YG1', 'YTQ_BTY1', 'YTQ_MDY1', 'YTQU_TA1', 'YTQ_BTT1', 'YTQ_MDT1', 'YTQU_QG1', 'YTQ_BTQ1', 'YTQ_MDQ1']
In [8]:
#create reduced dataframe
In [9]:
#create reduced dataframe
health_red = health_df[['SEX',	'R_MARITL',	'MRACRPI2',	'REGION',	'PAR_STAT',	'DOINGLWA',	'SUPERVIS',	'WRKCATA',	'HOURPDA',	'PDSICKA',	'WRKLYR4',	'HYPEV',	'HYBPLEV',	'CHLEV',	'CHDEV',	'MIEV',	'STREV',	'COPDEV',	'AASMEV',	'ULCEV',	'CANEV',	'DBHVPAY',	'DBHVCLY',	'DBHVWLY',	'DBHVPAN',	'DBHVCLN',	'DBHVWLN',	'DIBREL',	'DIBEV1',	'DIBPRE2',	'EPILEP1',	'AHAYFYR',	'SINYR',	'CBRCHYR',	'KIDWKYR',	'LIVYR',	'JNTSYMP',	'ARTH1',	'PAINECK',	'PAINLB',	'PAINFACE',	'AMIGR',	'ACOLD2W',	'AINTIL2W',	'AHEARST1',	'AVISION',	'VIM_GLEV',	'VIM_MDEV',	'VIMGLASS',	'AVISACT',	'CHPAIN6M',	'AHSTATYR',	'FLA1AR',	'SPECEQ',	'ALC1YR',	'CIGAREV2',	'ECIGEV2',	'SMKSTAT2',	'APLKIND',	'AWORPAY',	'ADNLONG2',	'ASRGYR',	'AMDLONGR',	'HIT1A',	'HIT2A',	'HIT3A',	'HIT4A',	'FLUVACYR',	'LIVEV',	'ASICPUSE',	'ASIRETR',	'ASIMEDC',	'ASISTLV',	'ASICNHC',	'AWEBUSE',	'YTQU_YG1','ALCSTAT','YRSWRKPA',	'ASISLEEP',	'AHEIGHT',	'AWEIGHTP',	'BMI',	'BEDDAYR',	'CLCKTP',	'AGE_P',	'AHCNOYR2',	'LOCALL1B']]
In [10]:
#recode race
health_red['MRACRPI2'] = health_red['MRACRPI2'].replace([9,10,11,15,16,17], 4)
C:\Users\lenovo\Anaconda2\lib\site-packages\ipykernel_launcher.py:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  
In [11]:
health_red['MRACRPI2'].value_counts().plot(kind='bar')
Out[11]:
<matplotlib.axes._subplots.AxesSubplot at 0xdae18d0>
In [12]:
health_red.columns.get_loc("R_MARITL")
Out[12]:
1
In [13]:
#recode marital status
health_red['R_MARITL'] = health_red['R_MARITL'].replace([2,3], 1) #married
C:\Users\lenovo\Anaconda2\lib\site-packages\ipykernel_launcher.py:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  
In [14]:
health_red['R_MARITL'] = health_red['R_MARITL'].replace([4], 2) #widowed
C:\Users\lenovo\Anaconda2\lib\site-packages\ipykernel_launcher.py:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  """Entry point for launching an IPython kernel.
In [15]:
health_red['R_MARITL'] = health_red['R_MARITL'].replace([5,6], 3) #divorced
C:\Users\lenovo\Anaconda2\lib\site-packages\ipykernel_launcher.py:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  """Entry point for launching an IPython kernel.
In [16]:
health_red['R_MARITL'] = health_red['R_MARITL'].replace([7,8,9], 4) #never married
C:\Users\lenovo\Anaconda2\lib\site-packages\ipykernel_launcher.py:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  """Entry point for launching an IPython kernel.
In [17]:
health_red['R_MARITL'].value_counts().plot(kind='bar')
Out[17]:
<matplotlib.axes._subplots.AxesSubplot at 0xdae1898>
In [18]:
#recode missing values in part of dataframe
health_nan = health_red.iloc[:,0:76].replace([7,8,9], np.nan)
health_nan2 = health_red.iloc[:,76]
health_nan3 = pd.concat([health_nan,health_nan2],axis=1,join_axes=[health_nan.index])
health_nan3.head()
Out[18]:
SEX R_MARITL MRACRPI2 REGION PAR_STAT DOINGLWA SUPERVIS WRKCATA HOURPDA PDSICKA ... FLUVACYR LIVEV ASICPUSE ASIRETR ASIMEDC ASISTLV ASICNHC AWEBUSE YTQU_YG1 ALCSTAT
0 2 2 1 3 3 5.0 2.0 1.0 1.0 2.0 ... 1.0 2.0 4.0 3.0 4.0 4.0 4.0 1.0 2.0 6
1 1 4 1 2 3 5.0 2.0 1.0 1.0 2.0 ... 1.0 2.0 4.0 3.0 3.0 3.0 3.0 1.0 2.0 7
2 1 1 1 2 1 1.0 2.0 1.0 1.0 1.0 ... 2.0 2.0 3.0 3.0 2.0 2.0 3.0 1.0 2.0 6
3 2 3 1 2 3 1.0 2.0 1.0 1.0 1.0 ... 1.0 2.0 4.0 2.0 4.0 4.0 4.0 1.0 1.0 6
4 1 1 1 3 1 1.0 1.0 1.0 1.0 1.0 ... 2.0 2.0 4.0 1.0 1.0 3.0 2.0 1.0 1.0 6

5 rows × 77 columns

In [19]:
health_nan3.shape
Out[19]:
(26742, 77)
In [20]:
#recode values in rest of dataframe to merge
health_rest = health_red.iloc[:,77:87].replace([96,97,98,99,996,997,998,999,9999], np.nan)
health_rest.head()
Out[20]:
YRSWRKPA ASISLEEP AHEIGHT AWEIGHTP BMI BEDDAYR CLCKTP AGE_P AHCNOYR2 LOCALL1B
0 28.0 8.0 61.0 155.0 2930.0 0.0 4 65 2.0 5.0
1 0.0 6.0 74.0 180.0 2309.0 3.0 9 19 2.0 NaN
2 13.0 5.0 69.0 240.0 3544.0 4.0 3 45 0.0 8.0
3 13.0 8.0 62.0 236.0 4313.0 6.0 1 67 3.0 6.0
4 16.0 8.0 63.0 182.0 3227.0 0.0 3 40 2.0 9.0
In [21]:
health_rest.shape
Out[21]:
(26742, 10)
In [22]:
#merge dataframes with values 7,8,9,96,97,98,99,996,997,998,999,9999 recoded to NaN
mergedf=pd.concat([health_nan3,health_rest],axis=1,join_axes=[health_nan3.index])
mergedf.head()
Out[22]:
SEX R_MARITL MRACRPI2 REGION PAR_STAT DOINGLWA SUPERVIS WRKCATA HOURPDA PDSICKA ... YRSWRKPA ASISLEEP AHEIGHT AWEIGHTP BMI BEDDAYR CLCKTP AGE_P AHCNOYR2 LOCALL1B
0 2 2 1 3 3 5.0 2.0 1.0 1.0 2.0 ... 28.0 8.0 61.0 155.0 2930.0 0.0 4 65 2.0 5.0
1 1 4 1 2 3 5.0 2.0 1.0 1.0 2.0 ... 0.0 6.0 74.0 180.0 2309.0 3.0 9 19 2.0 NaN
2 1 1 1 2 1 1.0 2.0 1.0 1.0 1.0 ... 13.0 5.0 69.0 240.0 3544.0 4.0 3 45 0.0 8.0
3 2 3 1 2 3 1.0 2.0 1.0 1.0 1.0 ... 13.0 8.0 62.0 236.0 4313.0 6.0 1 67 3.0 6.0
4 1 1 1 3 1 1.0 1.0 1.0 1.0 1.0 ... 16.0 8.0 63.0 182.0 3227.0 0.0 3 40 2.0 9.0

5 rows × 87 columns

In [23]:
mergedf['LOCALL1B'].shape
Out[23]:
(26742L,)
In [24]:
#test.isna().sum()
print(mergedf.isna().sum().to_string())
SEX            0
R_MARITL       0
MRACRPI2       0
REGION         0
PAR_STAT       0
DOINGLWA      10
SUPERVIS    1212
WRKCATA     1302
HOURPDA     1285
PDSICKA     1529
WRKLYR4       40
HYPEV         36
HYBPLEV      831
CHLEV        112
CHDEV         56
MIEV          20
STREV         20
COPDEV        36
AASMEV        22
ULCEV         30
CANEV         19
DBHVPAY       35
DBHVCLY       32
DBHVWLY       25
DBHVPAN       21
DBHVCLN       27
DBHVWLN       14
DIBREL       405
DIBEV1        20
DIBPRE2     2839
EPILEP1       13
AHAYFYR       28
SINYR         31
CBRCHYR       19
KIDWKYR       20
LIVYR         17
JNTSYMP       19
ARTH1         36
PAINECK       20
PAINLB        15
PAINFACE      14
AMIGR         15
ACOLD2W       16
AINTIL2W      14
AHEARST1       8
AVISION        9
VIM_GLEV      46
VIM_MDEV      53
VIMGLASS     128
AVISACT       13
CHPAIN6M      42
AHSTATYR      26
FLA1AR         0
SPECEQ         9
ALC1YR       194
CIGAREV2     106
ECIGEV2       92
SMKSTAT2      99
APLKIND     3348
AWORPAY      285
ADNLONG2     357
ASRGYR       330
AMDLONGR     364
HIT1A        356
HIT2A        347
HIT3A        352
HIT4A        355
FLUVACYR     451
LIVEV        443
ASICPUSE     582
ASIRETR      731
ASIMEDC      715
ASISTLV      713
ASICNHC      711
AWEBUSE      890
YTQU_YG1     837
ALCSTAT        0
YRSWRKPA    1408
ASISLEEP     844
AHEIGHT     1853
AWEIGHTP    2426
BMI          924
BEDDAYR      212
CLCKTP         0
AGE_P          0
AHCNOYR2     392
LOCALL1B    2271
In [25]:
#remove NAs
health_na = mergedf.dropna()
In [26]:
#check number of NAs
health_na.isnull().sum().sum()
Out[26]:
0
In [27]:
health_na.shape
Out[27]:
(15913, 87)
In [28]:
health_na['LOCALL1B'].shape
Out[28]:
(15913L,)
In [29]:
health_na['ASISLEEP'].value_counts().plot(kind='bar')
Out[29]:
<matplotlib.axes._subplots.AxesSubplot at 0x1a013438>
In [30]:
health_na['ASISLEEP'].hist()
Out[30]:
<matplotlib.axes._subplots.AxesSubplot at 0x125ceeb8>
In [31]:
health_na.describe()
Out[31]:
SEX R_MARITL MRACRPI2 REGION PAR_STAT DOINGLWA SUPERVIS WRKCATA HOURPDA PDSICKA ... YRSWRKPA ASISLEEP AHEIGHT AWEIGHTP BMI BEDDAYR CLCKTP AGE_P AHCNOYR2 LOCALL1B
count 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000 ... 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000 15913.000000
mean 1.560171 2.211337 1.282473 2.650035 2.470433 2.462201 1.632879 1.760887 1.451706 1.386162 ... 11.317979 7.043926 66.759693 174.755986 2749.213787 4.477283 3.224408 50.862188 2.732294 4.780431
std 0.496382 1.286954 0.737698 1.018002 0.864585 1.875317 0.482035 1.351432 0.497678 0.486884 ... 10.756068 1.285489 3.881437 38.444969 530.688215 24.796872 1.492853 17.992640 2.129829 2.528555
min 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 ... 0.000000 1.000000 59.000000 100.000000 1522.000000 0.000000 0.000000 18.000000 0.000000 1.000000
25% 1.000000 1.000000 1.000000 2.000000 2.000000 1.000000 1.000000 1.000000 1.000000 1.000000 ... 2.000000 6.000000 64.000000 145.000000 2366.000000 0.000000 3.000000 36.000000 1.000000 3.000000
50% 2.000000 2.000000 1.000000 3.000000 3.000000 1.000000 2.000000 1.000000 1.000000 1.000000 ... 8.000000 7.000000 66.000000 170.000000 2662.000000 0.000000 3.000000 51.000000 2.000000 4.000000
75% 2.000000 4.000000 1.000000 3.000000 3.000000 5.000000 2.000000 2.000000 2.000000 2.000000 ... 18.000000 8.000000 70.000000 200.000000 3056.000000 2.000000 4.000000 65.000000 4.000000 7.000000
max 2.000000 4.000000 4.000000 4.000000 3.000000 5.000000 2.000000 6.000000 2.000000 2.000000 ... 35.000000 20.000000 76.000000 299.000000 5274.000000 365.000000 9.000000 85.000000 8.000000 9.000000

8 rows × 87 columns

In [32]:
health_na[health_na.columns[0]].value_counts().plot(kind='bar')
Out[32]:
<matplotlib.axes._subplots.AxesSubplot at 0x145b0c18>
In [33]:
health_na[health_na.columns[1]].value_counts().plot(kind='bar')
Out[33]:
<matplotlib.axes._subplots.AxesSubplot at 0x186bafd0>
In [34]:
health_na[health_na.columns[2]].value_counts().plot(kind='bar')
Out[34]:
<matplotlib.axes._subplots.AxesSubplot at 0x186baef0>
In [35]:
health_na[health_na.columns[3]].value_counts().plot(kind='bar')
Out[35]:
<matplotlib.axes._subplots.AxesSubplot at 0x186dfcc0>
In [36]:
health_na[health_na.columns[4]].value_counts().plot(kind='bar')
Out[36]:
<matplotlib.axes._subplots.AxesSubplot at 0x14c79748>
In [37]:
health_na[health_na.columns[5]].value_counts().plot(kind='bar')
Out[37]:
<matplotlib.axes._subplots.AxesSubplot at 0x14c79940>
In [38]:
#plot all variables
# matplotlib.style.use('ggplot')
# health_na.plot.bar(subplots=True)
In [39]:
#save data frame without NAs to csv file
health_na.to_csv('health_na.csv', sep=",")
In [40]:
#create reduced categorical dataframe
health_cat = health_na[['SEX',	'R_MARITL',	'MRACRPI2',	'REGION',	'PAR_STAT',	'DOINGLWA',	'SUPERVIS',	'WRKCATA',	'HOURPDA',	'PDSICKA',	'WRKLYR4',	'HYPEV',	'HYBPLEV',	'CHLEV',	'CHDEV',	'MIEV',	'STREV',	'COPDEV',	'AASMEV',	'ULCEV',	'CANEV',	'DBHVPAY',	'DBHVCLY',	'DBHVWLY',	'DBHVPAN',	'DBHVCLN',	'DBHVWLN',	'DIBREL',	'DIBEV1',	'DIBPRE2',	'EPILEP1',	'AHAYFYR',	'SINYR',	'CBRCHYR',	'KIDWKYR',	'LIVYR',	'JNTSYMP',	'ARTH1',	'PAINECK',	'PAINLB',	'PAINFACE',	'AMIGR',	'ACOLD2W',	'AINTIL2W',	'AHEARST1',	'AVISION',	'VIM_GLEV',	'VIM_MDEV',	'VIMGLASS',	'AVISACT',	'CHPAIN6M',	'AHSTATYR',	'FLA1AR',	'SPECEQ',	'ALC1YR',	'CIGAREV2',	'ECIGEV2',	'SMKSTAT2',	'APLKIND',	'AWORPAY',	'ADNLONG2',	'ASRGYR',	'AMDLONGR',	'HIT1A',	'HIT2A',	'HIT3A',	'HIT4A',	'FLUVACYR',	'LIVEV',	'ASICPUSE',	'ASIRETR',	'ASIMEDC',	'ASISTLV',	'ASICNHC',	'AWEBUSE',	'YTQU_YG1',	'ALCSTAT']]
In [41]:
health_cat.head()
Out[41]:
SEX R_MARITL MRACRPI2 REGION PAR_STAT DOINGLWA SUPERVIS WRKCATA HOURPDA PDSICKA ... FLUVACYR LIVEV ASICPUSE ASIRETR ASIMEDC ASISTLV ASICNHC AWEBUSE YTQU_YG1 ALCSTAT
0 2 2 1 3 3 5.0 2.0 1.0 1.0 2.0 ... 1.0 2.0 4.0 3.0 4.0 4.0 4.0 1.0 2.0 6
2 1 1 1 2 1 1.0 2.0 1.0 1.0 1.0 ... 2.0 2.0 3.0 3.0 2.0 2.0 3.0 1.0 2.0 6
3 2 3 1 2 3 1.0 2.0 1.0 1.0 1.0 ... 1.0 2.0 4.0 2.0 4.0 4.0 4.0 1.0 1.0 6
4 1 1 1 3 1 1.0 1.0 1.0 1.0 1.0 ... 2.0 2.0 4.0 1.0 1.0 3.0 2.0 1.0 1.0 6
6 2 3 1 2 3 5.0 1.0 5.0 2.0 2.0 ... 1.0 2.0 2.0 2.0 3.0 3.0 4.0 1.0 2.0 6

5 rows × 77 columns

In [42]:
#check number of NAs
health_cat.isnull().sum().sum()
Out[42]:
0
In [43]:
health_cat.shape
Out[43]:
(15913, 77)
In [44]:
#create reduced numerical dataframe
health_num = health_na[['YRSWRKPA',	'ASISLEEP',	'AHEIGHT',	'AWEIGHTP',	'BMI',	'BEDDAYR',	'CLCKTP',	'AGE_P',	'AHCNOYR2',	'LOCALL1B']]
In [45]:
health_num.head()
Out[45]:
YRSWRKPA ASISLEEP AHEIGHT AWEIGHTP BMI BEDDAYR CLCKTP AGE_P AHCNOYR2 LOCALL1B
0 28.0 8.0 61.0 155.0 2930.0 0.0 4 65 2.0 5.0
2 13.0 5.0 69.0 240.0 3544.0 4.0 3 45 0.0 8.0
3 13.0 8.0 62.0 236.0 4313.0 6.0 1 67 3.0 6.0
4 16.0 8.0 63.0 182.0 3227.0 0.0 3 40 2.0 9.0
6 22.0 7.0 62.0 135.0 2467.0 0.0 3 79 2.0 3.0
In [46]:
health_num['LOCALL1B'].shape
Out[46]:
(15913L,)
In [47]:
#check number of NAs
health_num.isnull().sum().sum()
Out[47]:
0
In [48]:
plt.show(health_num.boxplot(column=['YRSWRKPA',	'ASISLEEP',	'AHEIGHT','AWEIGHTP']))
In [49]:
plt.show(health_num.boxplot(column=['BMI']))
In [50]:
plt.show(health_num.boxplot(column=['BEDDAYR',	'CLCKTP',	'AGE_P',	'AHCNOYR2',	'LOCALL1B']))
In [51]:
# # z-score standard
# zscore = lambda x: ((x - x.mean()) / x.std()) if (x.dtypes==np.float64 or x.dtypes==np.int64) else x
# health_num_std = health_num.copy()
# health_num_std.apply(zscore).head()
In [52]:
#min max normalization of numerical variables
x = health_num.values #returns a numpy array
min_max_scaler = preprocessing.MinMaxScaler()
x_scaled = min_max_scaler.fit_transform(x)
health_num_norm = pd.DataFrame(x_scaled, columns=health_num.columns)
health_num_norm.head()
Out[52]:
YRSWRKPA ASISLEEP AHEIGHT AWEIGHTP BMI BEDDAYR CLCKTP AGE_P AHCNOYR2 LOCALL1B
0 0.800000 0.368421 0.117647 0.276382 0.375267 0.000000 0.444444 0.701493 0.250 0.500
1 0.371429 0.210526 0.588235 0.703518 0.538913 0.010959 0.333333 0.402985 0.000 0.875
2 0.371429 0.368421 0.176471 0.683417 0.743870 0.016438 0.111111 0.731343 0.375 0.625
3 0.457143 0.368421 0.235294 0.412060 0.454424 0.000000 0.333333 0.328358 0.250 1.000
4 0.628571 0.315789 0.176471 0.175879 0.251866 0.000000 0.333333 0.910448 0.250 0.250
In [53]:
health_num_norm['LOCALL1B'].shape
Out[53]:
(15913L,)
In [54]:
#check number of NAs
health_num_norm.isnull().sum()
Out[54]:
YRSWRKPA    0
ASISLEEP    0
AHEIGHT     0
AWEIGHTP    0
BMI         0
BEDDAYR     0
CLCKTP      0
AGE_P       0
AHCNOYR2    0
LOCALL1B    0
dtype: int64
In [55]:
plt.show(health_num_norm.boxplot(column=['YRSWRKPA',	'ASISLEEP',	'AHEIGHT',	'AWEIGHTP',	'BMI',	'BEDDAYR',	'CLCKTP',	'AGE_P',	'AHCNOYR2',	'LOCALL1B']))
In [56]:
#check for correlatin between numerical variables
health_num_norm.corr()
Out[56]:
YRSWRKPA ASISLEEP AHEIGHT AWEIGHTP BMI BEDDAYR CLCKTP AGE_P AHCNOYR2 LOCALL1B
YRSWRKPA 1.000000 0.073681 0.029057 0.032787 0.018463 -0.000990 -0.034424 0.611988 0.064160 0.077594
ASISLEEP 0.073681 1.000000 -0.002255 -0.048063 -0.052960 -0.014005 -0.014601 0.107165 -0.010235 -0.036978
AHEIGHT 0.029057 -0.002255 1.000000 0.508214 -0.029413 -0.041522 -0.007406 -0.088707 -0.104406 0.018310
AWEIGHTP 0.032787 -0.048063 0.508214 1.000000 0.840354 -0.008086 -0.034245 -0.022113 -0.015722 0.026511
BMI 0.018463 -0.052960 -0.029413 0.840354 1.000000 0.018737 -0.033768 0.026152 0.046096 0.021117
BEDDAYR -0.000990 -0.014005 -0.041522 -0.008086 0.018737 1.000000 0.005201 0.038757 0.203062 -0.017649
CLCKTP -0.034424 -0.014601 -0.007406 -0.034245 -0.033768 0.005201 1.000000 -0.040367 -0.058527 -0.008623
AGE_P 0.611988 0.107165 -0.088707 -0.022113 0.026152 0.038757 -0.040367 1.000000 0.149908 0.014379
AHCNOYR2 0.064160 -0.010235 -0.104406 -0.015722 0.046096 0.203062 -0.058527 0.149908 1.000000 0.013778
LOCALL1B 0.077594 -0.036978 0.018310 0.026511 0.021117 -0.017649 -0.008623 0.014379 0.013778 1.000000
In [57]:
pd.plotting.scatter_matrix(health_num_norm, figsize=(16, 16), alpha = 0.2)
plt.show()
In [58]:
plt.figure(figsize=(10,10))
sns.heatmap(health_num_norm.corr(), cmap='BuGn')
Out[58]:
<matplotlib.axes._subplots.AxesSubplot at 0x14de5a90>
In [59]:
#avr weight and avr height are higly correlated
#age and age on the job is correlated
#drop avr weight and age
health_num_norm_drop = health_num_norm.drop("AWEIGHTP",axis=1)
In [60]:
health_num_norm_drop['LOCALL1B'].shape
Out[60]:
(15913L,)
In [61]:
#check number of NAs
health_num_norm_drop.isnull().sum().sum()
Out[61]:
0
In [62]:
#drop age
health_num_norm_drop = health_num_norm_drop.drop("AGE_P",axis=1)
In [63]:
#check number of NAs
health_num_norm_drop.isnull().sum().sum()
Out[63]:
0
In [64]:
#Plot correlation
sns.heatmap(health_num_norm_drop.corr(), cmap='BuGn')
Out[64]:
<matplotlib.axes._subplots.AxesSubplot at 0x16140cf8>
In [65]:
#re-run correlations
health_num_norm_drop.corr()
Out[65]:
YRSWRKPA ASISLEEP AHEIGHT BMI BEDDAYR CLCKTP AHCNOYR2 LOCALL1B
YRSWRKPA 1.000000 0.073681 0.029057 0.018463 -0.000990 -0.034424 0.064160 0.077594
ASISLEEP 0.073681 1.000000 -0.002255 -0.052960 -0.014005 -0.014601 -0.010235 -0.036978
AHEIGHT 0.029057 -0.002255 1.000000 -0.029413 -0.041522 -0.007406 -0.104406 0.018310
BMI 0.018463 -0.052960 -0.029413 1.000000 0.018737 -0.033768 0.046096 0.021117
BEDDAYR -0.000990 -0.014005 -0.041522 0.018737 1.000000 0.005201 0.203062 -0.017649
CLCKTP -0.034424 -0.014601 -0.007406 -0.033768 0.005201 1.000000 -0.058527 -0.008623
AHCNOYR2 0.064160 -0.010235 -0.104406 0.046096 0.203062 -0.058527 1.000000 0.013778
LOCALL1B 0.077594 -0.036978 0.018310 0.021117 -0.017649 -0.008623 0.013778 1.000000
In [66]:
#save health_num_norm_drop to csv file
health_num_norm_drop.to_csv('health_num_norm_drop.csv', sep=",")
In [67]:
health_num_norm_drop.shape
Out[67]:
(15913, 8)
In [68]:
#force conversion to categorical varibles
health_cat = health_cat.astype('category')
In [69]:
print(health_cat.dtypes.to_string())
SEX         category
R_MARITL    category
MRACRPI2    category
REGION      category
PAR_STAT    category
DOINGLWA    category
SUPERVIS    category
WRKCATA     category
HOURPDA     category
PDSICKA     category
WRKLYR4     category
HYPEV       category
HYBPLEV     category
CHLEV       category
CHDEV       category
MIEV        category
STREV       category
COPDEV      category
AASMEV      category
ULCEV       category
CANEV       category
DBHVPAY     category
DBHVCLY     category
DBHVWLY     category
DBHVPAN     category
DBHVCLN     category
DBHVWLN     category
DIBREL      category
DIBEV1      category
DIBPRE2     category
EPILEP1     category
AHAYFYR     category
SINYR       category
CBRCHYR     category
KIDWKYR     category
LIVYR       category
JNTSYMP     category
ARTH1       category
PAINECK     category
PAINLB      category
PAINFACE    category
AMIGR       category
ACOLD2W     category
AINTIL2W    category
AHEARST1    category
AVISION     category
VIM_GLEV    category
VIM_MDEV    category
VIMGLASS    category
AVISACT     category
CHPAIN6M    category
AHSTATYR    category
FLA1AR      category
SPECEQ      category
ALC1YR      category
CIGAREV2    category
ECIGEV2     category
SMKSTAT2    category
APLKIND     category
AWORPAY     category
ADNLONG2    category
ASRGYR      category
AMDLONGR    category
HIT1A       category
HIT2A       category
HIT3A       category
HIT4A       category
FLUVACYR    category
LIVEV       category
ASICPUSE    category
ASIRETR     category
ASIMEDC     category
ASISTLV     category
ASICNHC     category
AWEBUSE     category
YTQU_YG1    category
ALCSTAT     category
In [70]:
health_cat['ALCSTAT'].shape
Out[70]:
(15913,)
In [71]:
health_dummy = pd.get_dummies(health_cat,drop_first=True)
health_dummy.reset_index(drop=True, inplace=True)
health_dummy.head()
Out[71]:
SEX_2 R_MARITL_2 R_MARITL_3 R_MARITL_4 MRACRPI2_2 MRACRPI2_3 MRACRPI2_4 REGION_2 REGION_3 REGION_4 ... AWEBUSE_2.0 YTQU_YG1_2.0 ALCSTAT_2 ALCSTAT_3 ALCSTAT_5 ALCSTAT_6 ALCSTAT_7 ALCSTAT_8 ALCSTAT_9 ALCSTAT_10
0 1 1 0 0 0 0 0 0 1 0 ... 0 1 0 0 0 1 0 0 0 0
1 0 0 0 0 0 0 0 1 0 0 ... 0 1 0 0 0 1 0 0 0 0
2 1 0 1 0 0 0 0 1 0 0 ... 0 0 0 0 0 1 0 0 0 0
3 0 0 0 0 0 0 0 0 1 0 ... 0 0 0 0 0 1 0 0 0 0
4 1 0 1 0 0 0 0 1 0 0 ... 0 1 0 0 0 1 0 0 0 0

5 rows × 135 columns

In [72]:
health_dummy['ALCSTAT_10'].shape
Out[72]:
(15913L,)
In [73]:
#check number of NAs
health_dummy.isnull().sum().sum()
Out[73]:
0
In [74]:
columnNamesDummy = list(health_dummy.head(0))
print(columnNamesDummy)
['SEX_2', 'R_MARITL_2', 'R_MARITL_3', 'R_MARITL_4', 'MRACRPI2_2', 'MRACRPI2_3', 'MRACRPI2_4', 'REGION_2', 'REGION_3', 'REGION_4', 'PAR_STAT_2', 'PAR_STAT_3', 'DOINGLWA_2.0', 'DOINGLWA_3.0', 'DOINGLWA_4.0', 'DOINGLWA_5.0', 'SUPERVIS_2.0', 'WRKCATA_2.0', 'WRKCATA_3.0', 'WRKCATA_4.0', 'WRKCATA_5.0', 'WRKCATA_6.0', 'HOURPDA_2.0', 'PDSICKA_2.0', 'WRKLYR4_1.0', 'WRKLYR4_2.0', 'HYPEV_2.0', 'HYBPLEV_2.0', 'HYBPLEV_3.0', 'HYBPLEV_4.0', 'HYBPLEV_5.0', 'CHLEV_2.0', 'CHDEV_2.0', 'MIEV_2.0', 'STREV_2.0', 'COPDEV_2.0', 'AASMEV_2.0', 'ULCEV_2.0', 'CANEV_2.0', 'DBHVPAY_2.0', 'DBHVCLY_2.0', 'DBHVWLY_2.0', 'DBHVPAN_2.0', 'DBHVCLN_2.0', 'DBHVWLN_2.0', 'DIBREL_2.0', 'DIBEV1_3.0', 'DIBPRE2_2.0', 'EPILEP1_2.0', 'AHAYFYR_2.0', 'SINYR_2.0', 'CBRCHYR_2.0', 'KIDWKYR_2.0', 'LIVYR_2.0', 'JNTSYMP_2.0', 'ARTH1_2.0', 'PAINECK_2.0', 'PAINLB_2.0', 'PAINFACE_2.0', 'AMIGR_2.0', 'ACOLD2W_2.0', 'AINTIL2W_2.0', 'AHEARST1_2.0', 'AHEARST1_3.0', 'AHEARST1_4.0', 'AHEARST1_5.0', 'AHEARST1_6.0', 'AVISION_2.0', 'VIM_GLEV_2.0', 'VIM_MDEV_2.0', 'VIMGLASS_2.0', 'AVISACT_2.0', 'CHPAIN6M_2.0', 'CHPAIN6M_3.0', 'CHPAIN6M_4.0', 'AHSTATYR_2.0', 'AHSTATYR_3.0', 'FLA1AR_2', 'FLA1AR_3', 'SPECEQ_2.0', 'ALC1YR_2.0', 'CIGAREV2_2.0', 'ECIGEV2_2.0', 'SMKSTAT2_2.0', 'SMKSTAT2_3.0', 'SMKSTAT2_4.0', 'APLKIND_2.0', 'APLKIND_3.0', 'APLKIND_4.0', 'APLKIND_5.0', 'APLKIND_6.0', 'AWORPAY_2.0', 'AWORPAY_3.0', 'ADNLONG2_1.0', 'ADNLONG2_2.0', 'ADNLONG2_3.0', 'ADNLONG2_4.0', 'ADNLONG2_5.0', 'ASRGYR_2.0', 'AMDLONGR_1.0', 'AMDLONGR_2.0', 'AMDLONGR_3.0', 'AMDLONGR_4.0', 'AMDLONGR_5.0', 'HIT1A_2.0', 'HIT2A_2.0', 'HIT3A_2.0', 'HIT4A_2.0', 'FLUVACYR_2.0', 'LIVEV_2.0', 'ASICPUSE_2.0', 'ASICPUSE_3.0', 'ASICPUSE_4.0', 'ASIRETR_2.0', 'ASIRETR_3.0', 'ASIRETR_4.0', 'ASIMEDC_2.0', 'ASIMEDC_3.0', 'ASIMEDC_4.0', 'ASISTLV_2.0', 'ASISTLV_3.0', 'ASISTLV_4.0', 'ASICNHC_2.0', 'ASICNHC_3.0', 'ASICNHC_4.0', 'AWEBUSE_2.0', 'YTQU_YG1_2.0', 'ALCSTAT_2', 'ALCSTAT_3', 'ALCSTAT_5', 'ALCSTAT_6', 'ALCSTAT_7', 'ALCSTAT_8', 'ALCSTAT_9', 'ALCSTAT_10']
In [75]:
#save dummy variables to csv file
health_dummy.to_csv('health_dummy.csv', sep=",")
In [76]:
health_dummy.shape
Out[76]:
(15913, 135)
In [77]:
health_num.shape
Out[77]:
(15913, 10)
In [78]:
health_num.isnull().sum().sum()
Out[78]:
0
In [79]:
#reset index for health_num
health_num.reset_index(drop=True, inplace=True)
In [80]:
#merge categorical dummy with numerical non-normalized
health_cleaned=pd.concat([health_dummy,health_num],axis=1,join_axes=[health_dummy.index])
health_cleaned.tail()
Out[80]:
SEX_2 R_MARITL_2 R_MARITL_3 R_MARITL_4 MRACRPI2_2 MRACRPI2_3 MRACRPI2_4 REGION_2 REGION_3 REGION_4 ... YRSWRKPA ASISLEEP AHEIGHT AWEIGHTP BMI BEDDAYR CLCKTP AGE_P AHCNOYR2 LOCALL1B
15908 1 1 0 0 0 0 0 0 0 0 ... 30.0 7.0 63.0 112.0 1984.0 30.0 3 78 8.0 4.0
15909 1 0 0 0 0 0 0 0 0 1 ... 1.0 8.0 66.0 127.0 2051.0 0.0 3 80 4.0 3.0
15910 1 1 0 0 0 0 0 0 1 0 ... 2.0 8.0 67.0 230.0 3601.0 1.0 3 70 2.0 4.0
15911 1 0 0 0 1 0 0 0 1 0 ... 18.0 7.0 64.0 220.0 3775.0 0.0 3 66 3.0 3.0
15912 1 0 0 0 0 0 0 0 1 0 ... 6.0 8.0 66.0 115.0 1858.0 2.0 4 69 4.0 6.0

5 rows × 145 columns

In [81]:
# #merge categorical dummy with numerical normalized
# health_cleaned=pd.concat([health_dummy,health_num_norm_drop],axis=1,join_axes=[health_dummy.index])
# health_cleaned.tail()
In [82]:
health_cleaned['LOCALL1B'].shape
Out[82]:
(15913L,)
In [83]:
health_cleaned['SEX_2'].shape
Out[83]:
(15913L,)
In [84]:
health_cleaned.shape
Out[84]:
(15913, 145)
In [85]:
#save health cleaned to csv file
health_cleaned.to_csv('health_cleaned.csv', sep=",")
In [86]:
#Y ->'DBHVPAY_2.0' =  Told to increase physical activity, past 12 m
In [87]:
#create  dataframe
health_cl = health_cleaned[['DBHVPAY_2.0',	'SEX_2',	'R_MARITL_2',	'R_MARITL_3',	'R_MARITL_4',	'MRACRPI2_2',	'MRACRPI2_3',	'MRACRPI2_4',	'REGION_2',	'REGION_3',	'REGION_4',	'PAR_STAT_2',	'PAR_STAT_3',	'DOINGLWA_2.0',	'DOINGLWA_3.0',	'DOINGLWA_4.0',	'DOINGLWA_5.0',	'SUPERVIS_2.0',	'WRKCATA_2.0',	'WRKCATA_3.0',	'WRKCATA_4.0',	'WRKCATA_5.0',	'WRKCATA_6.0',	'HOURPDA_2.0',	'PDSICKA_2.0',	'WRKLYR4_1.0',	'WRKLYR4_2.0',	'HYPEV_2.0',	'HYBPLEV_2.0',	'HYBPLEV_3.0',	'HYBPLEV_4.0',	'HYBPLEV_5.0',	'CHLEV_2.0',	'CHDEV_2.0',	'MIEV_2.0',	'STREV_2.0',	'COPDEV_2.0',	'AASMEV_2.0',	'ULCEV_2.0',	'CANEV_2.0',	'DBHVCLY_2.0',	'DBHVWLY_2.0',	'DBHVPAN_2.0',	'DBHVCLN_2.0',	'DBHVWLN_2.0',	'DIBREL_2.0',	'DIBEV1_3.0',	'DIBPRE2_2.0',	'EPILEP1_2.0',	'AHAYFYR_2.0',	'SINYR_2.0',	'CBRCHYR_2.0',	'KIDWKYR_2.0',	'LIVYR_2.0',	'JNTSYMP_2.0',	'ARTH1_2.0',	'PAINECK_2.0',	'PAINLB_2.0',	'PAINFACE_2.0',	'AMIGR_2.0',	'ACOLD2W_2.0',	'AINTIL2W_2.0',	'AHEARST1_2.0',	'AHEARST1_3.0',	'AHEARST1_4.0',	'AHEARST1_5.0',	'AHEARST1_6.0',	'AVISION_2.0',	'VIM_GLEV_2.0',	'VIM_MDEV_2.0',	'VIMGLASS_2.0',	'AVISACT_2.0',	'CHPAIN6M_2.0',	'CHPAIN6M_3.0',	'CHPAIN6M_4.0',	'AHSTATYR_2.0',	'AHSTATYR_3.0',	'FLA1AR_2',	'FLA1AR_3',	'SPECEQ_2.0',	'ALC1YR_2.0',	'CIGAREV2_2.0',	'ECIGEV2_2.0',	'SMKSTAT2_2.0',	'SMKSTAT2_3.0',	'SMKSTAT2_4.0',	'APLKIND_2.0',	'APLKIND_3.0',	'APLKIND_4.0',	'APLKIND_5.0',	'APLKIND_6.0',	'AWORPAY_2.0',	'AWORPAY_3.0',	'ADNLONG2_1.0',	'ADNLONG2_2.0',	'ADNLONG2_3.0',	'ADNLONG2_4.0',	'ADNLONG2_5.0',	'ASRGYR_2.0',	'AMDLONGR_1.0',	'AMDLONGR_2.0',	'AMDLONGR_3.0',	'AMDLONGR_4.0',	'AMDLONGR_5.0',	'HIT1A_2.0',	'HIT2A_2.0',	'HIT3A_2.0',	'HIT4A_2.0',	'FLUVACYR_2.0',	'LIVEV_2.0',	'ASICPUSE_2.0',	'ASICPUSE_3.0',	'ASICPUSE_4.0',	'ASIRETR_2.0',	'ASIRETR_3.0',	'ASIRETR_4.0',	'ASIMEDC_2.0',	'ASIMEDC_3.0',	'ASIMEDC_4.0',	'ASISTLV_2.0',	'ASISTLV_3.0',	'ASISTLV_4.0',	'ASICNHC_2.0',	'ASICNHC_3.0',	'ASICNHC_4.0',	'AWEBUSE_2.0',	'YTQU_YG1_2.0',	'ALCSTAT_2',	'ALCSTAT_3',	'ALCSTAT_5',	'ALCSTAT_6',	'ALCSTAT_7',	'ALCSTAT_8',	'ALCSTAT_9',	'ALCSTAT_10',	'YRSWRKPA',	'ASISLEEP',	'AHEIGHT',	'BMI',	'BEDDAYR',	'CLCKTP',	'AHCNOYR2',	'LOCALL1B']]
health_cl['DBHVPAY_2.0'].head()
Out[87]:
0    0
1    1
2    0
3    1
4    1
Name: DBHVPAY_2.0, dtype: uint8
In [88]:
#recode 'DBHVPAY_2.0' so 1 means Yes
physical = pd.get_dummies(health_cl['DBHVPAY_2.0'])
physical.columns = ["phys_yes", "phys_no"]
physical = physical.drop(columns=['phys_no'])
physical.head()
Out[88]:
phys_yes
0 1
1 0
2 1
3 0
4 0
In [89]:
#repalce 'phys_yes' with 'DBHVPAY_YES'
health_tree=pd.concat([physical,health_cl],axis=1,join_axes=[physical.index])
health_tree = health_tree.drop(columns=['DBHVPAY_2.0'])
health_tree.columns.values[0] = "DBHVPAY_YES"
health_tree.head()
Out[89]:
DBHVPAY_YES SEX_2 R_MARITL_2 R_MARITL_3 R_MARITL_4 MRACRPI2_2 MRACRPI2_3 MRACRPI2_4 REGION_2 REGION_3 ... ALCSTAT_9 ALCSTAT_10 YRSWRKPA ASISLEEP AHEIGHT BMI BEDDAYR CLCKTP AHCNOYR2 LOCALL1B
0 1 1 1 0 0 0 0 0 0 1 ... 0 0 28.0 8.0 61.0 2930.0 0.0 4 2.0 5.0
1 0 0 0 0 0 0 0 0 1 0 ... 0 0 13.0 5.0 69.0 3544.0 4.0 3 0.0 8.0
2 1 1 0 1 0 0 0 0 1 0 ... 0 0 13.0 8.0 62.0 4313.0 6.0 1 3.0 6.0
3 0 0 0 0 0 0 0 0 0 1 ... 0 0 16.0 8.0 63.0 3227.0 0.0 3 2.0 9.0
4 0 1 0 1 0 0 0 0 1 0 ... 0 0 22.0 7.0 62.0 2467.0 0.0 3 2.0 3.0

5 rows × 143 columns

In [90]:
health_tree_drop = health_tree
In [91]:
#column names
health_names = health_tree_drop.columns.values
health_names
Out[91]:
array(['DBHVPAY_YES', 'SEX_2', 'R_MARITL_2', 'R_MARITL_3', 'R_MARITL_4',
       'MRACRPI2_2', 'MRACRPI2_3', 'MRACRPI2_4', 'REGION_2', 'REGION_3',
       'REGION_4', 'PAR_STAT_2', 'PAR_STAT_3', 'DOINGLWA_2.0',
       'DOINGLWA_3.0', 'DOINGLWA_4.0', 'DOINGLWA_5.0', 'SUPERVIS_2.0',
       'WRKCATA_2.0', 'WRKCATA_3.0', 'WRKCATA_4.0', 'WRKCATA_5.0',
       'WRKCATA_6.0', 'HOURPDA_2.0', 'PDSICKA_2.0', 'WRKLYR4_1.0',
       'WRKLYR4_2.0', 'HYPEV_2.0', 'HYBPLEV_2.0', 'HYBPLEV_3.0',
       'HYBPLEV_4.0', 'HYBPLEV_5.0', 'CHLEV_2.0', 'CHDEV_2.0', 'MIEV_2.0',
       'STREV_2.0', 'COPDEV_2.0', 'AASMEV_2.0', 'ULCEV_2.0', 'CANEV_2.0',
       'DBHVCLY_2.0', 'DBHVWLY_2.0', 'DBHVPAN_2.0', 'DBHVCLN_2.0',
       'DBHVWLN_2.0', 'DIBREL_2.0', 'DIBEV1_3.0', 'DIBPRE2_2.0',
       'EPILEP1_2.0', 'AHAYFYR_2.0', 'SINYR_2.0', 'CBRCHYR_2.0',
       'KIDWKYR_2.0', 'LIVYR_2.0', 'JNTSYMP_2.0', 'ARTH1_2.0',
       'PAINECK_2.0', 'PAINLB_2.0', 'PAINFACE_2.0', 'AMIGR_2.0',
       'ACOLD2W_2.0', 'AINTIL2W_2.0', 'AHEARST1_2.0', 'AHEARST1_3.0',
       'AHEARST1_4.0', 'AHEARST1_5.0', 'AHEARST1_6.0', 'AVISION_2.0',
       'VIM_GLEV_2.0', 'VIM_MDEV_2.0', 'VIMGLASS_2.0', 'AVISACT_2.0',
       'CHPAIN6M_2.0', 'CHPAIN6M_3.0', 'CHPAIN6M_4.0', 'AHSTATYR_2.0',
       'AHSTATYR_3.0', 'FLA1AR_2', 'FLA1AR_3', 'SPECEQ_2.0', 'ALC1YR_2.0',
       'CIGAREV2_2.0', 'ECIGEV2_2.0', 'SMKSTAT2_2.0', 'SMKSTAT2_3.0',
       'SMKSTAT2_4.0', 'APLKIND_2.0', 'APLKIND_3.0', 'APLKIND_4.0',
       'APLKIND_5.0', 'APLKIND_6.0', 'AWORPAY_2.0', 'AWORPAY_3.0',
       'ADNLONG2_1.0', 'ADNLONG2_2.0', 'ADNLONG2_3.0', 'ADNLONG2_4.0',
       'ADNLONG2_5.0', 'ASRGYR_2.0', 'AMDLONGR_1.0', 'AMDLONGR_2.0',
       'AMDLONGR_3.0', 'AMDLONGR_4.0', 'AMDLONGR_5.0', 'HIT1A_2.0',
       'HIT2A_2.0', 'HIT3A_2.0', 'HIT4A_2.0', 'FLUVACYR_2.0', 'LIVEV_2.0',
       'ASICPUSE_2.0', 'ASICPUSE_3.0', 'ASICPUSE_4.0', 'ASIRETR_2.0',
       'ASIRETR_3.0', 'ASIRETR_4.0', 'ASIMEDC_2.0', 'ASIMEDC_3.0',
       'ASIMEDC_4.0', 'ASISTLV_2.0', 'ASISTLV_3.0', 'ASISTLV_4.0',
       'ASICNHC_2.0', 'ASICNHC_3.0', 'ASICNHC_4.0', 'AWEBUSE_2.0',
       'YTQU_YG1_2.0', 'ALCSTAT_2', 'ALCSTAT_3', 'ALCSTAT_5', 'ALCSTAT_6',
       'ALCSTAT_7', 'ALCSTAT_8', 'ALCSTAT_9', 'ALCSTAT_10', 'YRSWRKPA',
       'ASISLEEP', 'AHEIGHT', 'BMI', 'BEDDAYR', 'CLCKTP', 'AHCNOYR2',
       'LOCALL1B'], dtype=object)
In [92]:
y = health_tree_drop['DBHVPAY_YES'] # y variable
X = health_tree_drop[health_names[1:]]
X.head()
Out[92]:
SEX_2 R_MARITL_2 R_MARITL_3 R_MARITL_4 MRACRPI2_2 MRACRPI2_3 MRACRPI2_4 REGION_2 REGION_3 REGION_4 ... ALCSTAT_9 ALCSTAT_10 YRSWRKPA ASISLEEP AHEIGHT BMI BEDDAYR CLCKTP AHCNOYR2 LOCALL1B
0 1 1 0 0 0 0 0 0 1 0 ... 0 0 28.0 8.0 61.0 2930.0 0.0 4 2.0 5.0
1 0 0 0 0 0 0 0 1 0 0 ... 0 0 13.0 5.0 69.0 3544.0 4.0 3 0.0 8.0
2 1 0 1 0 0 0 0 1 0 0 ... 0 0 13.0 8.0 62.0 4313.0 6.0 1 3.0 6.0
3 0 0 0 0 0 0 0 0 1 0 ... 0 0 16.0 8.0 63.0 3227.0 0.0 3 2.0 9.0
4 1 0 1 0 0 0 0 1 0 0 ... 0 0 22.0 7.0 62.0 2467.0 0.0 3 2.0 3.0

5 rows × 142 columns

In [93]:
y.head
Out[93]:
<bound method Series.head of 0        1
1        0
2        1
3        0
4        0
5        0
6        0
7        1
8        1
9        0
10       0
11       0
12       0
13       0
14       0
15       0
16       0
17       0
18       1
19       1
20       1
21       0
22       1
23       0
24       1
25       1
26       0
27       0
28       0
29       0
        ..
15883    0
15884    0
15885    0
15886    1
15887    1
15888    0
15889    0
15890    0
15891    0
15892    0
15893    1
15894    0
15895    0
15896    0
15897    1
15898    1
15899    0
15900    1
15901    0
15902    0
15903    1
15904    1
15905    0
15906    0
15907    0
15908    0
15909    0
15910    1
15911    1
15912    0
Name: DBHVPAY_YES, Length: 15913, dtype: uint8>
In [94]:
#create train and test sets
from sklearn.cross_validation import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=99874)
print "X_train", X_train.shape
print "y_train", y_train.shape
print "X_test", X_test.shape
print "y_test", y_test.shape
X_train (12730, 142)
y_train (12730L,)
X_test (3183, 142)
y_test (3183L,)
In [95]:
############################################################################################

#Decistion Tree

############################################################################################
In [96]:
treeclf = tree.DecisionTreeClassifier(criterion='entropy', min_samples_split=3)
treeclf = treeclf.fit(X_train, y_train)
In [97]:
#A versatile function to measure performance of a classification model
from sklearn import metrics

def measure_performance(X, y, clf, show_accuracy=True, show_classification_report=True, show_confussion_matrix=True):
    y_pred = clf.predict(X)   
    if show_accuracy:
         print "Accuracy:{0:.3f}".format(metrics.accuracy_score(y, y_pred)),"\n"
    if show_classification_report:
        print "Classification report"
        print metrics.classification_report(y, y_pred),"\n"
      
    if show_confussion_matrix:
        print "Confussion matrix"
        print metrics.confusion_matrix(y, y_pred),"\n"
In [98]:
measure_performance(X_test, y_test, treeclf, show_confussion_matrix=True, show_classification_report=True)
Accuracy:0.712 

Classification report
             precision    recall  f1-score   support

          0       0.79      0.78      0.78      2140
          1       0.56      0.57      0.56      1043

avg / total       0.71      0.71      0.71      3183


Confussion matrix
[[1670  470]
 [ 448  595]] 

In [99]:
#predictions
treepreds_test = treeclf.predict(X_test)
print treepreds_test
[0 1 0 ... 0 0 1]
In [100]:
#classification report
print(classification_report(y_test, treepreds_test))
             precision    recall  f1-score   support

          0       0.79      0.78      0.78      2140
          1       0.56      0.57      0.56      1043

avg / total       0.71      0.71      0.71      3183

In [101]:
treecm = confusion_matrix(y_test, treepreds_test)
print treecm
[[1670  470]
 [ 448  595]]
In [102]:
print treeclf.score(X_test, y_test)
print treeclf.score(X_train, y_train)
0.7115928369462771
0.9979575805184603
In [103]:
export_graphviz(treeclf,out_file='tree.dot', feature_names=X_train.columns, class_names=["No","Yes"])

with open("tree.dot") as f:
    dot_graph = f.read()
graphviz.Source(dot_graph)
Out[103]:
Tree 0 DBHVCLY_2.0 <= 0.5 entropy = 0.916 samples = 12730 value = [8520, 4210] class = No 1 BMI <= 2815.5 entropy = 0.77 samples = 3188 value = [718, 2470] class = Yes 0->1 True 984 FLA1AR_2 <= 0.5 entropy = 0.685 samples = 9542 value = [7802, 1740] class = No 0->984 False 2 DBHVPAN_2.0 <= 0.5 entropy = 0.916 samples = 1032 value = [342, 690] class = Yes 1->2 369 DBHVWLY_2.0 <= 0.5 entropy = 0.668 samples = 2156 value = [376, 1780] class = Yes 1->369 3 CANEV_2.0 <= 0.5 entropy = 0.854 samples = 709 value = [198, 511] class = Yes 2->3 244 ASISTLV_4.0 <= 0.5 entropy = 0.992 samples = 323 value = [144, 179] class = Yes 2->244 4 ASICPUSE_4.0 <= 0.5 entropy = 0.988 samples = 87 value = [38, 49] class = Yes 3->4 35 AHCNOYR2 <= 5.5 entropy = 0.823 samples = 622 value = [160, 462] class = Yes 3->35 5 SUPERVIS_2.0 <= 0.5 entropy = 0.918 samples = 21 value = [14, 7] class = No 4->5 12 DBHVCLN_2.0 <= 0.5 entropy = 0.946 samples = 66 value = [24, 42] class = Yes 4->12 6 REGION_3 <= 0.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 5->6 11 entropy = 0.0 samples = 8 value = [8, 0] class = No 5->11 7 AHAYFYR_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 6->7 10 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 6->10 8 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 7->8 9 entropy = 0.0 samples = 6 value = [6, 0] class = No 7->9 13 ASIRETR_2.0 <= 0.5 entropy = 0.873 samples = 58 value = [17, 41] class = Yes 12->13 32 BEDDAYR <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 12->32 14 WRKCATA_4.0 <= 0.5 entropy = 0.959 samples = 42 value = [16, 26] class = Yes 13->14 29 LOCALL1B <= 1.5 entropy = 0.337 samples = 16 value = [1, 15] class = Yes 13->29 15 ADNLONG2_2.0 <= 0.5 entropy = 0.878 samples = 37 value = [11, 26] class = Yes 14->15 28 entropy = 0.0 samples = 5 value = [5, 0] class = No 14->28 16 SMKSTAT2_4.0 <= 0.5 entropy = 0.758 samples = 32 value = [7, 25] class = Yes 15->16 25 AHEARST1_6.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 15->25 17 AHSTATYR_3.0 <= 0.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 16->17 22 CLCKTP <= 2.5 entropy = 0.286 samples = 20 value = [1, 19] class = Yes 16->22 18 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 17->18 19 BEDDAYR <= 3.0 entropy = 0.811 samples = 8 value = [6, 2] class = No 17->19 20 entropy = 0.0 samples = 6 value = [6, 0] class = No 19->20 21 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 19->21 23 entropy = 0.0 samples = 1 value = [1, 0] class = No 22->23 24 entropy = 0.0 samples = 19 value = [0, 19] class = Yes 22->24 26 entropy = 0.0 samples = 4 value = [4, 0] class = No 25->26 27 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 25->27 30 entropy = 0.0 samples = 1 value = [1, 0] class = No 29->30 31 entropy = 0.0 samples = 15 value = [0, 15] class = Yes 29->31 33 entropy = 0.0 samples = 7 value = [7, 0] class = No 32->33 34 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 32->34 36 DBHVWLN_2.0 <= 0.5 entropy = 0.851 samples = 546 value = [151, 395] class = Yes 35->36 229 LOCALL1B <= 3.5 entropy = 0.525 samples = 76 value = [9, 67] class = Yes 35->229 37 FLUVACYR_2.0 <= 0.5 entropy = 0.498 samples = 64 value = [7, 57] class = Yes 36->37 52 LOCALL1B <= 1.5 entropy = 0.88 samples = 482 value = [144, 338] class = Yes 36->52 38 AHEIGHT <= 65.5 entropy = 0.669 samples = 40 value = [7, 33] class = Yes 37->38 51 entropy = 0.0 samples = 24 value = [0, 24] class = Yes 37->51 39 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 38->39 40 AHCNOYR2 <= 1.5 entropy = 0.797 samples = 29 value = [7, 22] class = Yes 38->40 41 entropy = 0.0 samples = 2 value = [2, 0] class = No 40->41 42 AHEIGHT <= 68.5 entropy = 0.691 samples = 27 value = [5, 22] class = Yes 40->42 43 HIT4A_2.0 <= 0.5 entropy = 0.918 samples = 15 value = [5, 10] class = Yes 42->43 50 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 42->50 44 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 43->44 45 SEX_2 <= 0.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 43->45 46 entropy = 0.0 samples = 3 value = [3, 0] class = No 45->46 47 PAINECK_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 45->47 48 entropy = 0.0 samples = 2 value = [2, 0] class = No 47->48 49 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 47->49 53 SEX_2 <= 0.5 entropy = 1.0 samples = 36 value = [18, 18] class = No 52->53 68 BEDDAYR <= 18.0 entropy = 0.859 samples = 446 value = [126, 320] class = Yes 52->68 54 BMI <= 2580.5 entropy = 0.811 samples = 16 value = [4, 12] class = Yes 53->54 61 ASICNHC_3.0 <= 0.5 entropy = 0.881 samples = 20 value = [14, 6] class = No 53->61 55 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 54->55 56 SMKSTAT2_3.0 <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 54->56 57 DOINGLWA_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 56->57 60 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 56->60 58 entropy = 0.0 samples = 4 value = [4, 0] class = No 57->58 59 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 57->59 62 ADNLONG2_2.0 <= 0.5 entropy = 0.391 samples = 13 value = [12, 1] class = No 61->62 65 AHEARST1_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 61->65 63 entropy = 0.0 samples = 12 value = [12, 0] class = No 62->63 64 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 62->64 66 entropy = 0.0 samples = 2 value = [2, 0] class = No 65->66 67 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 65->67 69 APLKIND_5.0 <= 0.5 entropy = 0.87 samples = 433 value = [126, 307] class = Yes 68->69 228 entropy = 0.0 samples = 13 value = [0, 13] class = Yes 68->228 70 R_MARITL_2 <= 0.5 entropy = 0.86 samples = 427 value = [121, 306] class = Yes 69->70 225 ASIMEDC_3.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 69->225 71 AHEIGHT <= 64.5 entropy = 0.836 samples = 391 value = [104, 287] class = Yes 70->71 208 AHEIGHT <= 62.5 entropy = 0.998 samples = 36 value = [17, 19] class = Yes 70->208 72 DIBPRE2_2.0 <= 0.5 entropy = 0.686 samples = 126 value = [23, 103] class = Yes 71->72 111 BMI <= 2510.5 entropy = 0.888 samples = 265 value = [81, 184] class = Yes 71->111 73 entropy = 0.0 samples = 16 value = [0, 16] class = Yes 72->73 74 ASISTLV_4.0 <= 0.5 entropy = 0.74 samples = 110 value = [23, 87] class = Yes 72->74 75 BMI <= 2135.0 entropy = 0.581 samples = 72 value = [10, 62] class = Yes 74->75 96 PAR_STAT_3 <= 0.5 entropy = 0.927 samples = 38 value = [13, 25] class = Yes 74->96 76 AWEBUSE_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 75->76 79 ASIRETR_2.0 <= 0.5 entropy = 0.444 samples = 65 value = [6, 59] class = Yes 75->79 77 entropy = 0.0 samples = 4 value = [4, 0] class = No 76->77 78 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 76->78 80 AHCNOYR2 <= 1.5 entropy = 0.639 samples = 37 value = [6, 31] class = Yes 79->80 95 entropy = 0.0 samples = 28 value = [0, 28] class = Yes 79->95 81 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 80->81 82 BMI <= 2334.0 entropy = 0.779 samples = 26 value = [6, 20] class = Yes 80->82 83 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 82->83 84 BMI <= 2388.0 entropy = 0.881 samples = 20 value = [6, 14] class = Yes 82->84 85 entropy = 0.0 samples = 2 value = [2, 0] class = No 84->85 86 AHEIGHT <= 62.5 entropy = 0.764 samples = 18 value = [4, 14] class = Yes 84->86 87 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 86->87 88 YRSWRKPA <= 2.0 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 86->88 89 entropy = 0.0 samples = 2 value = [2, 0] class = No 88->89 90 AHCNOYR2 <= 2.5 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 88->90 91 ASISTLV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 90->91 94 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 90->94 92 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 91->92 93 entropy = 0.0 samples = 2 value = [2, 0] class = No 91->93 97 HOURPDA_2.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 96->97 102 CLCKTP <= 3.5 entropy = 0.706 samples = 26 value = [5, 21] class = Yes 96->102 98 entropy = 0.0 samples = 5 value = [5, 0] class = No 97->98 99 ALCSTAT_5 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 97->99 100 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 99->100 101 entropy = 0.0 samples = 3 value = [3, 0] class = No 99->101 103 ASICNHC_2.0 <= 0.5 entropy = 0.439 samples = 22 value = [2, 20] class = Yes 102->103 108 FLUVACYR_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 102->108 104 LOCALL1B <= 8.5 entropy = 0.276 samples = 21 value = [1, 20] class = Yes 103->104 107 entropy = 0.0 samples = 1 value = [1, 0] class = No 103->107 105 entropy = 0.0 samples = 20 value = [0, 20] class = Yes 104->105 106 entropy = 0.0 samples = 1 value = [1, 0] class = No 104->106 109 entropy = 0.0 samples = 3 value = [3, 0] class = No 108->109 110 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 108->110 112 AHEIGHT <= 73.5 entropy = 0.976 samples = 98 value = [40, 58] class = Yes 111->112 149 HYPEV_2.0 <= 0.5 entropy = 0.804 samples = 167 value = [41, 126] class = Yes 111->149 113 AMIGR_2.0 <= 0.5 entropy = 0.993 samples = 89 value = [40, 49] class = Yes 112->113 148 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 112->148 114 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 113->114 115 VIMGLASS_2.0 <= 0.5 entropy = 1.0 samples = 82 value = [40, 42] class = Yes 113->115 116 DBHVCLN_2.0 <= 0.5 entropy = 0.987 samples = 60 value = [34, 26] class = No 115->116 139 AHEIGHT <= 71.5 entropy = 0.845 samples = 22 value = [6, 16] class = Yes 115->139 117 LOCALL1B <= 4.5 entropy = 1.0 samples = 52 value = [26, 26] class = No 116->117 138 entropy = 0.0 samples = 8 value = [8, 0] class = No 116->138 118 AHSTATYR_3.0 <= 0.5 entropy = 0.845 samples = 22 value = [6, 16] class = Yes 117->118 125 AHEARST1_2.0 <= 0.5 entropy = 0.918 samples = 30 value = [20, 10] class = No 117->125 119 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 118->119 120 CIGAREV2_2.0 <= 0.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 118->120 121 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 120->121 122 AHAYFYR_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 120->122 123 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 122->123 124 entropy = 0.0 samples = 6 value = [6, 0] class = No 122->124 126 YRSWRKPA <= 5.5 entropy = 0.544 samples = 16 value = [14, 2] class = No 125->126 131 WRKLYR4_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [6, 8] class = Yes 125->131 127 CHPAIN6M_4.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 126->127 130 entropy = 0.0 samples = 11 value = [11, 0] class = No 126->130 128 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 127->128 129 entropy = 0.0 samples = 3 value = [3, 0] class = No 127->129 132 YRSWRKPA <= 20.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 131->132 137 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 131->137 133 entropy = 0.0 samples = 5 value = [5, 0] class = No 132->133 134 HYPEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 132->134 135 entropy = 0.0 samples = 1 value = [1, 0] class = No 134->135 136 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 134->136 140 ADNLONG2_3.0 <= 0.5 entropy = 0.544 samples = 16 value = [2, 14] class = Yes 139->140 145 HOURPDA_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 139->145 141 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 140->141 142 FLUVACYR_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 140->142 143 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 142->143 144 entropy = 0.0 samples = 2 value = [2, 0] class = No 142->144 146 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 145->146 147 entropy = 0.0 samples = 4 value = [4, 0] class = No 145->147 150 AMDLONGR_2.0 <= 0.5 entropy = 0.525 samples = 59 value = [7, 52] class = Yes 149->150 167 AHAYFYR_2.0 <= 0.5 entropy = 0.899 samples = 108 value = [34, 74] class = Yes 149->167 151 HYBPLEV_5.0 <= 0.5 entropy = 0.376 samples = 55 value = [4, 51] class = Yes 150->151 164 AVISION_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 150->164 152 LOCALL1B <= 2.5 entropy = 0.31 samples = 54 value = [3, 51] class = Yes 151->152 163 entropy = 0.0 samples = 1 value = [1, 0] class = No 151->163 153 REGION_3 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 152->153 158 SMKSTAT2_2.0 <= 0.5 entropy = 0.149 samples = 47 value = [1, 46] class = Yes 152->158 154 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 153->154 155 R_MARITL_3 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 153->155 156 entropy = 0.0 samples = 2 value = [2, 0] class = No 155->156 157 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 155->157 159 entropy = 0.0 samples = 44 value = [0, 44] class = Yes 158->159 160 ACOLD2W_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 158->160 161 entropy = 0.0 samples = 1 value = [1, 0] class = No 160->161 162 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 160->162 165 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 164->165 166 entropy = 0.0 samples = 3 value = [3, 0] class = No 164->166 168 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 167->168 169 ALCSTAT_8 <= 0.5 entropy = 0.931 samples = 98 value = [34, 64] class = Yes 167->169 170 WRKCATA_3.0 <= 0.5 entropy = 0.911 samples = 95 value = [31, 64] class = Yes 169->170 207 entropy = 0.0 samples = 3 value = [3, 0] class = No 169->207 171 WRKCATA_5.0 <= 0.5 entropy = 0.887 samples = 92 value = [28, 64] class = Yes 170->171 206 entropy = 0.0 samples = 3 value = [3, 0] class = No 170->206 172 ECIGEV2_2.0 <= 0.5 entropy = 0.85 samples = 87 value = [24, 63] class = Yes 171->172 203 PDSICKA_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 171->203 173 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 172->173 174 ADNLONG2_2.0 <= 0.5 entropy = 0.9 samples = 76 value = [24, 52] class = Yes 172->174 175 SINYR_2.0 <= 0.5 entropy = 0.798 samples = 62 value = [15, 47] class = Yes 174->175 198 BMI <= 2658.5 entropy = 0.94 samples = 14 value = [9, 5] class = No 174->198 176 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 175->176 177 ACOLD2W_2.0 <= 0.5 entropy = 0.86 samples = 53 value = [15, 38] class = Yes 175->177 178 ALCSTAT_7 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 177->178 181 DIBEV1_3.0 <= 0.5 entropy = 0.747 samples = 47 value = [10, 37] class = Yes 177->181 179 entropy = 0.0 samples = 5 value = [5, 0] class = No 178->179 180 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 178->180 182 CIGAREV2_2.0 <= 0.5 entropy = 0.675 samples = 45 value = [8, 37] class = Yes 181->182 197 entropy = 0.0 samples = 2 value = [2, 0] class = No 181->197 183 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 182->183 184 BEDDAYR <= 1.5 entropy = 0.787 samples = 34 value = [8, 26] class = Yes 182->184 185 YRSWRKPA <= 14.5 entropy = 0.696 samples = 32 value = [6, 26] class = Yes 184->185 196 entropy = 0.0 samples = 2 value = [2, 0] class = No 184->196 186 WRKLYR4_2.0 <= 0.5 entropy = 0.439 samples = 22 value = [2, 20] class = Yes 185->186 191 LOCALL1B <= 7.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 185->191 187 entropy = 0.0 samples = 19 value = [0, 19] class = Yes 186->187 188 CHPAIN6M_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 186->188 189 entropy = 0.0 samples = 2 value = [2, 0] class = No 188->189 190 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 188->190 192 ALCSTAT_2 <= 0.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 191->192 195 entropy = 0.0 samples = 3 value = [3, 0] class = No 191->195 193 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 192->193 194 entropy = 0.0 samples = 1 value = [1, 0] class = No 192->194 199 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 198->199 200 AWEBUSE_2.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 198->200 201 entropy = 0.0 samples = 9 value = [9, 0] class = No 200->201 202 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 200->202 204 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 203->204 205 entropy = 0.0 samples = 4 value = [4, 0] class = No 203->205 209 entropy = 0.0 samples = 5 value = [5, 0] class = No 208->209 210 ASISTLV_4.0 <= 0.5 entropy = 0.963 samples = 31 value = [12, 19] class = Yes 208->210 211 YTQU_YG1_2.0 <= 0.5 entropy = 0.567 samples = 15 value = [2, 13] class = Yes 210->211 216 AMDLONGR_2.0 <= 0.5 entropy = 0.954 samples = 16 value = [10, 6] class = No 210->216 212 AMDLONGR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 211->212 215 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 211->215 213 entropy = 0.0 samples = 2 value = [2, 0] class = No 212->213 214 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 212->214 217 AHCNOYR2 <= 1.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 216->217 224 entropy = 0.0 samples = 4 value = [4, 0] class = No 216->224 218 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 217->218 219 REGION_3 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 217->219 220 entropy = 0.0 samples = 5 value = [5, 0] class = No 219->220 221 AHCNOYR2 <= 2.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 219->221 222 entropy = 0.0 samples = 1 value = [1, 0] class = No 221->222 223 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 221->223 226 entropy = 0.0 samples = 5 value = [5, 0] class = No 225->226 227 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 225->227 230 entropy = 0.0 samples = 28 value = [0, 28] class = Yes 229->230 231 PDSICKA_2.0 <= 0.5 entropy = 0.696 samples = 48 value = [9, 39] class = Yes 229->231 232 BMI <= 2599.0 entropy = 0.33 samples = 33 value = [2, 31] class = Yes 231->232 239 BEDDAYR <= 1.0 entropy = 0.997 samples = 15 value = [7, 8] class = Yes 231->239 233 entropy = 0.0 samples = 24 value = [0, 24] class = Yes 232->233 234 BMI <= 2691.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 232->234 235 REGION_4 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 234->235 238 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 234->238 236 entropy = 0.0 samples = 2 value = [2, 0] class = No 235->236 237 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 235->237 240 entropy = 0.0 samples = 5 value = [5, 0] class = No 239->240 241 LOCALL1B <= 7.0 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 239->241 242 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 241->242 243 entropy = 0.0 samples = 2 value = [2, 0] class = No 241->243 245 DBHVCLN_2.0 <= 0.5 entropy = 0.956 samples = 220 value = [83, 137] class = Yes 244->245 328 CHLEV_2.0 <= 0.5 entropy = 0.975 samples = 103 value = [61, 42] class = No 244->328 246 SMKSTAT2_2.0 <= 0.5 entropy = 0.994 samples = 130 value = [59, 71] class = Yes 245->246 295 AHEARST1_5.0 <= 0.5 entropy = 0.837 samples = 90 value = [24, 66] class = Yes 245->295 247 ASICPUSE_2.0 <= 0.5 entropy = 0.985 samples = 124 value = [53, 71] class = Yes 246->247 294 entropy = 0.0 samples = 6 value = [6, 0] class = No 246->294 248 BEDDAYR <= 2.5 entropy = 0.998 samples = 110 value = [52, 58] class = Yes 247->248 291 MRACRPI2_2 <= 0.5 entropy = 0.371 samples = 14 value = [1, 13] class = Yes 247->291 249 FLUVACYR_2.0 <= 0.5 entropy = 0.953 samples = 75 value = [28, 47] class = Yes 248->249 278 WRKCATA_3.0 <= 0.5 entropy = 0.898 samples = 35 value = [24, 11] class = No 248->278 250 ADNLONG2_1.0 <= 0.5 entropy = 0.999 samples = 44 value = [23, 21] class = No 249->250 269 WRKLYR4_1.0 <= 0.5 entropy = 0.637 samples = 31 value = [5, 26] class = Yes 249->269 251 ASIRETR_3.0 <= 0.5 entropy = 0.9 samples = 19 value = [6, 13] class = Yes 250->251 260 AWEBUSE_2.0 <= 0.5 entropy = 0.904 samples = 25 value = [17, 8] class = No 250->260 252 AHEARST1_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [6, 8] class = Yes 251->252 259 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 251->259 253 YRSWRKPA <= 19.5 entropy = 0.845 samples = 11 value = [3, 8] class = Yes 252->253 258 entropy = 0.0 samples = 3 value = [3, 0] class = No 252->258 254 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 253->254 255 AHCNOYR2 <= 1.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 253->255 256 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 255->256 257 entropy = 0.0 samples = 3 value = [3, 0] class = No 255->257 261 YTQU_YG1_2.0 <= 0.5 entropy = 0.702 samples = 21 value = [17, 4] class = No 260->261 268 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 260->268 262 CHLEV_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 261->262 265 ECIGEV2_2.0 <= 0.5 entropy = 0.337 samples = 16 value = [15, 1] class = No 261->265 263 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 262->263 264 entropy = 0.0 samples = 2 value = [2, 0] class = No 262->264 266 entropy = 1.0 samples = 2 value = [1, 1] class = No 265->266 267 entropy = 0.0 samples = 14 value = [14, 0] class = No 265->267 270 ASICNHC_3.0 <= 0.5 entropy = 0.48 samples = 29 value = [3, 26] class = Yes 269->270 277 entropy = 0.0 samples = 2 value = [2, 0] class = No 269->277 271 entropy = 0.0 samples = 17 value = [0, 17] class = Yes 270->271 272 ASIRETR_2.0 <= 0.5 entropy = 0.811 samples = 12 value = [3, 9] class = Yes 270->272 273 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 272->273 274 DIBREL_2.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 272->274 275 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 274->275 276 entropy = 0.0 samples = 3 value = [3, 0] class = No 274->276 279 CHLEV_2.0 <= 0.5 entropy = 0.811 samples = 32 value = [24, 8] class = No 278->279 290 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 278->290 280 ASISLEEP <= 5.5 entropy = 0.469 samples = 20 value = [18, 2] class = No 279->280 285 PDSICKA_2.0 <= 0.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 279->285 281 CHPAIN6M_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 280->281 284 entropy = 0.0 samples = 15 value = [15, 0] class = No 280->284 282 entropy = 0.0 samples = 3 value = [3, 0] class = No 281->282 283 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 281->283 286 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 285->286 287 MRACRPI2_4 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 285->287 288 entropy = 0.0 samples = 6 value = [6, 0] class = No 287->288 289 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 287->289 292 entropy = 0.0 samples = 13 value = [0, 13] class = Yes 291->292 293 entropy = 0.0 samples = 1 value = [1, 0] class = No 291->293 296 SUPERVIS_2.0 <= 0.5 entropy = 0.811 samples = 88 value = [22, 66] class = Yes 295->296 327 entropy = 0.0 samples = 2 value = [2, 0] class = No 295->327 297 HIT3A_2.0 <= 0.5 entropy = 0.971 samples = 35 value = [14, 21] class = Yes 296->297 314 VIMGLASS_2.0 <= 0.5 entropy = 0.612 samples = 53 value = [8, 45] class = Yes 296->314 298 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 297->298 299 JNTSYMP_2.0 <= 0.5 entropy = 1.0 samples = 28 value = [14, 14] class = No 297->299 300 AWEBUSE_2.0 <= 0.5 entropy = 0.863 samples = 14 value = [4, 10] class = Yes 299->300 307 LOCALL1B <= 3.5 entropy = 0.863 samples = 14 value = [10, 4] class = No 299->307 301 AHCNOYR2 <= 3.5 entropy = 0.65 samples = 12 value = [2, 10] class = Yes 300->301 306 entropy = 0.0 samples = 2 value = [2, 0] class = No 300->306 302 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 301->302 303 CANEV_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 301->303 304 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 303->304 305 entropy = 0.0 samples = 2 value = [2, 0] class = No 303->305 308 entropy = 0.0 samples = 7 value = [7, 0] class = No 307->308 309 PAR_STAT_3 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 307->309 310 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 309->310 311 BMI <= 2755.0 entropy = 0.811 samples = 4 value = [3, 1] class = No 309->311 312 entropy = 0.0 samples = 3 value = [3, 0] class = No 311->312 313 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 311->313 315 LOCALL1B <= 1.5 entropy = 0.303 samples = 37 value = [2, 35] class = Yes 314->315 320 HYPEV_2.0 <= 0.5 entropy = 0.954 samples = 16 value = [6, 10] class = Yes 314->320 316 YRSWRKPA <= 19.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 315->316 319 entropy = 0.0 samples = 30 value = [0, 30] class = Yes 315->319 317 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 316->317 318 entropy = 0.0 samples = 2 value = [2, 0] class = No 316->318 321 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 320->321 322 AWORPAY_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 320->322 323 entropy = 0.0 samples = 5 value = [5, 0] class = No 322->323 324 YRSWRKPA <= 2.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 322->324 325 entropy = 0.0 samples = 1 value = [1, 0] class = No 324->325 326 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 324->326 329 BMI <= 2668.5 entropy = 0.998 samples = 57 value = [27, 30] class = Yes 328->329 354 AHEIGHT <= 65.5 entropy = 0.828 samples = 46 value = [34, 12] class = No 328->354 330 ASISLEEP <= 7.5 entropy = 0.979 samples = 41 value = [24, 17] class = No 329->330 349 ALCSTAT_3 <= 0.5 entropy = 0.696 samples = 16 value = [3, 13] class = Yes 329->349 331 CHDEV_2.0 <= 0.5 entropy = 0.629 samples = 19 value = [16, 3] class = No 330->331 338 LOCALL1B <= 4.5 entropy = 0.946 samples = 22 value = [8, 14] class = Yes 330->338 332 BMI <= 2644.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 331->332 335 LOCALL1B <= 1.5 entropy = 0.337 samples = 16 value = [15, 1] class = No 331->335 333 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 332->333 334 entropy = 0.0 samples = 1 value = [1, 0] class = No 332->334 336 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 335->336 337 entropy = 0.0 samples = 15 value = [15, 0] class = No 335->337 339 ALCSTAT_7 <= 0.5 entropy = 0.997 samples = 15 value = [8, 7] class = No 338->339 348 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 338->348 340 AHEARST1_2.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 339->340 347 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 339->347 341 PAINLB_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 340->341 346 entropy = 0.0 samples = 5 value = [5, 0] class = No 340->346 342 entropy = 0.0 samples = 2 value = [2, 0] class = No 341->342 343 AHEARST1_5.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 341->343 344 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 343->344 345 entropy = 0.0 samples = 1 value = [1, 0] class = No 343->345 350 ASICNHC_4.0 <= 0.5 entropy = 0.371 samples = 14 value = [1, 13] class = Yes 349->350 353 entropy = 0.0 samples = 2 value = [2, 0] class = No 349->353 351 entropy = 0.0 samples = 1 value = [1, 0] class = No 350->351 352 entropy = 0.0 samples = 13 value = [0, 13] class = Yes 350->352 355 ADNLONG2_1.0 <= 0.5 entropy = 0.918 samples = 12 value = [4, 8] class = Yes 354->355 362 HOURPDA_2.0 <= 0.5 entropy = 0.523 samples = 34 value = [30, 4] class = No 354->362 356 CHPAIN6M_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 355->356 361 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 355->361 357 entropy = 0.0 samples = 3 value = [3, 0] class = No 356->357 358 DIBEV1_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 356->358 359 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 358->359 360 entropy = 0.0 samples = 1 value = [1, 0] class = No 358->360 363 ASICPUSE_4.0 <= 0.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 362->363 368 entropy = 0.0 samples = 21 value = [21, 0] class = No 362->368 364 entropy = 0.0 samples = 8 value = [8, 0] class = No 363->364 365 REGION_2 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 363->365 366 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 365->366 367 entropy = 0.0 samples = 1 value = [1, 0] class = No 365->367 370 AHCNOYR2 <= 7.5 entropy = 0.426 samples = 667 value = [58, 609] class = Yes 369->370 491 BMI <= 3533.5 entropy = 0.748 samples = 1489 value = [318, 1171] class = Yes 369->491 371 AHEIGHT <= 60.5 entropy = 0.453 samples = 610 value = [58, 552] class = Yes 370->371 490 entropy = 0.0 samples = 57 value = [0, 57] class = Yes 370->490 372 entropy = 0.0 samples = 28 value = [0, 28] class = Yes 371->372 373 BMI <= 2914.0 entropy = 0.468 samples = 582 value = [58, 524] class = Yes 371->373 374 FLA1AR_2 <= 0.5 entropy = 0.769 samples = 40 value = [9, 31] class = Yes 373->374 387 BEDDAYR <= 3.5 entropy = 0.438 samples = 542 value = [49, 493] class = Yes 373->387 375 entropy = 0.0 samples = 14 value = [0, 14] class = Yes 374->375 376 REGION_2 <= 0.5 entropy = 0.931 samples = 26 value = [9, 17] class = Yes 374->376 377 CHDEV_2.0 <= 0.5 entropy = 0.722 samples = 20 value = [4, 16] class = Yes 376->377 384 AHEARST1_4.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 376->384 378 entropy = 0.0 samples = 2 value = [2, 0] class = No 377->378 379 ASISTLV_4.0 <= 0.5 entropy = 0.503 samples = 18 value = [2, 16] class = Yes 377->379 380 entropy = 0.0 samples = 14 value = [0, 14] class = Yes 379->380 381 DBHVWLN_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 379->381 382 entropy = 0.0 samples = 2 value = [2, 0] class = No 381->382 383 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 381->383 385 entropy = 0.0 samples = 5 value = [5, 0] class = No 384->385 386 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 384->386 388 WRKLYR4_2.0 <= 0.5 entropy = 0.474 samples = 453 value = [46, 407] class = Yes 387->388 481 ASISLEEP <= 14.5 entropy = 0.213 samples = 89 value = [3, 86] class = Yes 387->481 389 AHCNOYR2 <= 5.5 entropy = 0.399 samples = 341 value = [27, 314] class = Yes 388->389 448 CHLEV_2.0 <= 0.5 entropy = 0.657 samples = 112 value = [19, 93] class = Yes 388->448 390 SMKSTAT2_4.0 <= 0.5 entropy = 0.431 samples = 306 value = [27, 279] class = Yes 389->390 447 entropy = 0.0 samples = 35 value = [0, 35] class = Yes 389->447 391 DBHVPAN_2.0 <= 0.5 entropy = 0.579 samples = 116 value = [16, 100] class = Yes 390->391 420 SINYR_2.0 <= 0.5 entropy = 0.319 samples = 190 value = [11, 179] class = Yes 390->420 392 YRSWRKPA <= 2.5 entropy = 0.717 samples = 76 value = [15, 61] class = Yes 391->392 417 HYBPLEV_4.0 <= 0.5 entropy = 0.169 samples = 40 value = [1, 39] class = Yes 391->417 393 entropy = 0.0 samples = 16 value = [0, 16] class = Yes 392->393 394 ALCSTAT_7 <= 0.5 entropy = 0.811 samples = 60 value = [15, 45] class = Yes 392->394 395 ALCSTAT_2 <= 0.5 entropy = 0.896 samples = 48 value = [15, 33] class = Yes 394->395 416 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 394->416 396 BMI <= 3780.5 entropy = 0.859 samples = 46 value = [13, 33] class = Yes 395->396 415 entropy = 0.0 samples = 2 value = [2, 0] class = No 395->415 397 AHEARST1_2.0 <= 0.5 entropy = 0.722 samples = 35 value = [7, 28] class = Yes 396->397 410 ADNLONG2_1.0 <= 0.5 entropy = 0.994 samples = 11 value = [6, 5] class = No 396->410 398 LOCALL1B <= 7.5 entropy = 0.902 samples = 22 value = [7, 15] class = Yes 397->398 409 entropy = 0.0 samples = 13 value = [0, 13] class = Yes 397->409 399 YRSWRKPA <= 6.5 entropy = 0.989 samples = 16 value = [7, 9] class = Yes 398->399 408 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 398->408 400 AHSTATYR_3.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 399->400 403 CIGAREV2_2.0 <= 0.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 399->403 401 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 400->401 402 entropy = 0.0 samples = 5 value = [5, 0] class = No 400->402 404 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 403->404 405 AWORPAY_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 403->405 406 entropy = 0.0 samples = 2 value = [2, 0] class = No 405->406 407 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 405->407 411 entropy = 0.0 samples = 4 value = [4, 0] class = No 410->411 412 WRKCATA_4.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 410->412 413 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 412->413 414 entropy = 0.0 samples = 2 value = [2, 0] class = No 412->414 418 entropy = 0.0 samples = 39 value = [0, 39] class = Yes 417->418 419 entropy = 0.0 samples = 1 value = [1, 0] class = No 417->419 421 entropy = 0.0 samples = 39 value = [0, 39] class = Yes 420->421 422 R_MARITL_3 <= 0.5 entropy = 0.376 samples = 151 value = [11, 140] class = Yes 420->422 423 YRSWRKPA <= 1.5 entropy = 0.439 samples = 121 value = [11, 110] class = Yes 422->423 446 entropy = 0.0 samples = 30 value = [0, 30] class = Yes 422->446 424 AHCNOYR2 <= 2.5 entropy = 0.75 samples = 28 value = [6, 22] class = Yes 423->424 433 CHPAIN6M_4.0 <= 0.5 entropy = 0.302 samples = 93 value = [5, 88] class = Yes 423->433 425 DIBEV1_3.0 <= 0.5 entropy = 0.276 samples = 21 value = [1, 20] class = Yes 424->425 428 AHEIGHT <= 64.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 424->428 426 entropy = 0.0 samples = 19 value = [0, 19] class = Yes 425->426 427 entropy = 1.0 samples = 2 value = [1, 1] class = No 425->427 429 LOCALL1B <= 4.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 428->429 432 entropy = 0.0 samples = 4 value = [4, 0] class = No 428->432 430 entropy = 0.0 samples = 1 value = [1, 0] class = No 429->430 431 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 429->431 434 ALCSTAT_7 <= 0.5 entropy = 0.167 samples = 81 value = [2, 79] class = Yes 433->434 441 BEDDAYR <= 0.5 entropy = 0.811 samples = 12 value = [3, 9] class = Yes 433->441 435 entropy = 0.0 samples = 63 value = [0, 63] class = Yes 434->435 436 AMDLONGR_2.0 <= 0.5 entropy = 0.503 samples = 18 value = [2, 16] class = Yes 434->436 437 BMI <= 3839.5 entropy = 0.323 samples = 17 value = [1, 16] class = Yes 436->437 440 entropy = 0.0 samples = 1 value = [1, 0] class = No 436->440 438 entropy = 0.0 samples = 16 value = [0, 16] class = Yes 437->438 439 entropy = 0.0 samples = 1 value = [1, 0] class = No 437->439 442 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 441->442 443 AHCNOYR2 <= 2.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 441->443 444 entropy = 0.0 samples = 3 value = [3, 0] class = No 443->444 445 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 443->445 449 HYBPLEV_4.0 <= 0.5 entropy = 0.341 samples = 63 value = [4, 59] class = Yes 448->449 460 PAINFACE_2.0 <= 0.5 entropy = 0.889 samples = 49 value = [15, 34] class = Yes 448->460 450 AHCNOYR2 <= 5.5 entropy = 0.28 samples = 62 value = [3, 59] class = Yes 449->450 459 entropy = 0.0 samples = 1 value = [1, 0] class = No 449->459 451 AMDLONGR_2.0 <= 0.5 entropy = 0.133 samples = 54 value = [1, 53] class = Yes 450->451 456 CHPAIN6M_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 450->456 452 entropy = 0.0 samples = 47 value = [0, 47] class = Yes 451->452 453 REGION_4 <= 0.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 451->453 454 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 453->454 455 entropy = 0.0 samples = 1 value = [1, 0] class = No 453->455 457 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 456->457 458 entropy = 0.0 samples = 2 value = [2, 0] class = No 456->458 461 entropy = 0.0 samples = 3 value = [3, 0] class = No 460->461 462 ASISLEEP <= 6.5 entropy = 0.828 samples = 46 value = [12, 34] class = Yes 460->462 463 HYBPLEV_3.0 <= 0.5 entropy = 1.0 samples = 16 value = [8, 8] class = No 462->463 472 AHSTATYR_3.0 <= 0.5 entropy = 0.567 samples = 30 value = [4, 26] class = Yes 462->472 464 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 463->464 465 ASISTLV_3.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 463->465 466 AHCNOYR2 <= 3.5 entropy = 0.722 samples = 10 value = [8, 2] class = No 465->466 471 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 465->471 467 entropy = 0.0 samples = 6 value = [6, 0] class = No 466->467 468 HYPEV_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 466->468 469 entropy = 0.0 samples = 2 value = [2, 0] class = No 468->469 470 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 468->470 473 ALCSTAT_6 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 472->473 478 AMDLONGR_2.0 <= 0.5 entropy = 0.258 samples = 23 value = [1, 22] class = Yes 472->478 474 SINYR_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 473->474 477 entropy = 0.0 samples = 2 value = [2, 0] class = No 473->477 475 entropy = 0.0 samples = 1 value = [1, 0] class = No 474->475 476 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 474->476 479 entropy = 0.0 samples = 22 value = [0, 22] class = Yes 478->479 480 entropy = 0.0 samples = 1 value = [1, 0] class = No 478->480 482 LOCALL1B <= 7.5 entropy = 0.156 samples = 88 value = [2, 86] class = Yes 481->482 489 entropy = 0.0 samples = 1 value = [1, 0] class = No 481->489 483 entropy = 0.0 samples = 73 value = [0, 73] class = Yes 482->483 484 YRSWRKPA <= 13.5 entropy = 0.567 samples = 15 value = [2, 13] class = Yes 482->484 485 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 484->485 486 LOCALL1B <= 8.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 484->486 487 entropy = 0.0 samples = 2 value = [2, 0] class = No 486->487 488 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 486->488 492 DBHVPAN_2.0 <= 0.5 entropy = 0.795 samples = 1108 value = [266, 842] class = Yes 491->492 887 ALCSTAT_3 <= 0.5 entropy = 0.575 samples = 381 value = [52, 329] class = Yes 491->887 493 BMI <= 3503.5 entropy = 0.742 samples = 765 value = [161, 604] class = Yes 492->493 756 AHCNOYR2 <= 1.5 entropy = 0.889 samples = 343 value = [105, 238] class = Yes 492->756 494 HOURPDA_2.0 <= 0.5 entropy = 0.75 samples = 750 value = [161, 589] class = Yes 493->494 755 entropy = 0.0 samples = 15 value = [0, 15] class = Yes 493->755 495 AMDLONGR_3.0 <= 0.5 entropy = 0.812 samples = 411 value = [103, 308] class = Yes 494->495 650 ADNLONG2_3.0 <= 0.5 entropy = 0.66 samples = 339 value = [58, 281] class = Yes 494->650 496 WRKCATA_3.0 <= 0.5 entropy = 0.794 samples = 401 value = [96, 305] class = Yes 495->496 645 DIBREL_2.0 <= 0.5 entropy = 0.881 samples = 10 value = [7, 3] class = No 495->645 497 AHEIGHT <= 59.5 entropy = 0.81 samples = 381 value = [95, 286] class = Yes 496->497 642 AVISACT_2.0 <= 0.5 entropy = 0.286 samples = 20 value = [1, 19] class = Yes 496->642 498 R_MARITL_2 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 497->498 501 CHPAIN6M_4.0 <= 0.5 entropy = 0.798 samples = 376 value = [91, 285] class = Yes 497->501 499 entropy = 0.0 samples = 4 value = [4, 0] class = No 498->499 500 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 498->500 502 ASISLEEP <= 11.5 entropy = 0.829 samples = 325 value = [85, 240] class = Yes 501->502 629 AHCNOYR2 <= 4.5 entropy = 0.523 samples = 51 value = [6, 45] class = Yes 501->629 503 WRKCATA_2.0 <= 0.5 entropy = 0.822 samples = 323 value = [83, 240] class = Yes 502->503 628 entropy = 0.0 samples = 2 value = [2, 0] class = No 502->628 504 ASISLEEP <= 6.5 entropy = 0.801 samples = 308 value = [75, 233] class = Yes 503->504 621 APLKIND_2.0 <= 0.5 entropy = 0.997 samples = 15 value = [8, 7] class = No 503->621 505 DIBPRE2_2.0 <= 0.5 entropy = 0.639 samples = 105 value = [17, 88] class = Yes 504->505 534 HIT4A_2.0 <= 0.5 entropy = 0.863 samples = 203 value = [58, 145] class = Yes 504->534 506 entropy = 0.0 samples = 23 value = [0, 23] class = Yes 505->506 507 REGION_2 <= 0.5 entropy = 0.736 samples = 82 value = [17, 65] class = Yes 505->507 508 MRACRPI2_2 <= 0.5 entropy = 0.525 samples = 59 value = [7, 52] class = Yes 507->508 523 CHLEV_2.0 <= 0.5 entropy = 0.988 samples = 23 value = [10, 13] class = Yes 507->523 509 SMKSTAT2_4.0 <= 0.5 entropy = 0.327 samples = 50 value = [3, 47] class = Yes 508->509 518 AHEIGHT <= 65.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 508->518 510 LOCALL1B <= 4.5 entropy = 0.544 samples = 24 value = [3, 21] class = Yes 509->510 517 entropy = 0.0 samples = 26 value = [0, 26] class = Yes 509->517 511 entropy = 0.0 samples = 14 value = [0, 14] class = Yes 510->511 512 CIGAREV2_2.0 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 510->512 513 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 512->513 514 AHEIGHT <= 68.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 512->514 515 entropy = 0.0 samples = 3 value = [3, 0] class = No 514->515 516 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 514->516 519 CLCKTP <= 3.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 518->519 522 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 518->522 520 entropy = 0.0 samples = 4 value = [4, 0] class = No 519->520 521 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 519->521 524 BMI <= 3388.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 523->524 527 ALCSTAT_6 <= 0.5 entropy = 0.971 samples = 15 value = [9, 6] class = No 523->527 525 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 524->525 526 entropy = 0.0 samples = 1 value = [1, 0] class = No 524->526 528 ECIGEV2_2.0 <= 0.5 entropy = 0.722 samples = 10 value = [8, 2] class = No 527->528 531 BMI <= 2944.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 527->531 529 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 528->529 530 entropy = 0.0 samples = 8 value = [8, 0] class = No 528->530 532 entropy = 0.0 samples = 1 value = [1, 0] class = No 531->532 533 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 531->533 535 BMI <= 3071.0 entropy = 1.0 samples = 26 value = [13, 13] class = No 534->535 546 AINTIL2W_2.0 <= 0.5 entropy = 0.818 samples = 177 value = [45, 132] class = Yes 534->546 536 VIMGLASS_2.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 535->536 539 VIMGLASS_2.0 <= 0.5 entropy = 0.811 samples = 16 value = [4, 12] class = Yes 535->539 537 entropy = 0.0 samples = 9 value = [9, 0] class = No 536->537 538 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 536->538 540 AHEIGHT <= 69.5 entropy = 0.592 samples = 14 value = [2, 12] class = Yes 539->540 545 entropy = 0.0 samples = 2 value = [2, 0] class = No 539->545 541 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 540->541 542 HIT3A_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 540->542 543 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 542->543 544 entropy = 0.0 samples = 2 value = [2, 0] class = No 542->544 547 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 546->547 548 AHEIGHT <= 73.5 entropy = 0.838 samples = 168 value = [45, 123] class = Yes 546->548 549 BEDDAYR <= 11.0 entropy = 0.852 samples = 162 value = [45, 117] class = Yes 548->549 620 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 548->620 550 BEDDAYR <= 0.5 entropy = 0.835 samples = 158 value = [42, 116] class = Yes 549->550 617 PAR_STAT_3 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 549->617 551 DIBEV1_3.0 <= 0.5 entropy = 0.886 samples = 125 value = [38, 87] class = Yes 550->551 608 BEDDAYR <= 2.5 entropy = 0.533 samples = 33 value = [4, 29] class = Yes 550->608 552 SPECEQ_2.0 <= 0.5 entropy = 0.86 samples = 120 value = [34, 86] class = Yes 551->552 605 BMI <= 3063.0 entropy = 0.722 samples = 5 value = [4, 1] class = No 551->605 553 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 552->553 554 ALCSTAT_7 <= 0.5 entropy = 0.886 samples = 112 value = [34, 78] class = Yes 552->554 555 MIEV_2.0 <= 0.5 entropy = 0.918 samples = 96 value = [32, 64] class = Yes 554->555 600 LOCALL1B <= 2.5 entropy = 0.544 samples = 16 value = [2, 14] class = Yes 554->600 556 entropy = 0.0 samples = 2 value = [2, 0] class = No 555->556 557 AASMEV_2.0 <= 0.5 entropy = 0.903 samples = 94 value = [30, 64] class = Yes 555->557 558 CHLEV_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 557->558 563 LOCALL1B <= 7.5 entropy = 0.863 samples = 84 value = [24, 60] class = Yes 557->563 559 ADNLONG2_3.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 558->559 562 entropy = 0.0 samples = 4 value = [4, 0] class = No 558->562 560 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 559->560 561 entropy = 0.0 samples = 2 value = [2, 0] class = No 559->561 564 ASISLEEP <= 7.5 entropy = 0.787 samples = 68 value = [16, 52] class = Yes 563->564 591 CIGAREV2_2.0 <= 0.5 entropy = 1.0 samples = 16 value = [8, 8] class = No 563->591 565 ASICPUSE_4.0 <= 0.5 entropy = 0.952 samples = 35 value = [13, 22] class = Yes 564->565 582 APLKIND_3.0 <= 0.5 entropy = 0.439 samples = 33 value = [3, 30] class = Yes 564->582 566 SUPERVIS_2.0 <= 0.5 entropy = 0.592 samples = 14 value = [2, 12] class = Yes 565->566 569 BMI <= 2921.5 entropy = 0.998 samples = 21 value = [11, 10] class = No 565->569 567 entropy = 0.0 samples = 2 value = [2, 0] class = No 566->567 568 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 566->568 570 ADNLONG2_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 569->570 573 HYPEV_2.0 <= 0.5 entropy = 0.918 samples = 15 value = [10, 5] class = No 569->573 571 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 570->571 572 entropy = 0.0 samples = 1 value = [1, 0] class = No 570->572 574 AHEARST1_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 573->574 579 LOCALL1B <= 5.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 573->579 575 CLCKTP <= 3.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 574->575 578 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 574->578 576 entropy = 0.0 samples = 2 value = [2, 0] class = No 575->576 577 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 575->577 580 entropy = 0.0 samples = 8 value = [8, 0] class = No 579->580 581 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 579->581 583 AHCNOYR2 <= 0.5 entropy = 0.337 samples = 32 value = [2, 30] class = Yes 582->583 590 entropy = 0.0 samples = 1 value = [1, 0] class = No 582->590 584 entropy = 0.0 samples = 1 value = [1, 0] class = No 583->584 585 DIBPRE2_2.0 <= 0.5 entropy = 0.206 samples = 31 value = [1, 30] class = Yes 583->585 586 R_MARITL_2 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 585->586 589 entropy = 0.0 samples = 28 value = [0, 28] class = Yes 585->589 587 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 586->587 588 entropy = 0.0 samples = 1 value = [1, 0] class = No 586->588 592 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 591->592 593 CANEV_2.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 591->593 594 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 593->594 595 AWORPAY_2.0 <= 0.5 entropy = 0.722 samples = 10 value = [8, 2] class = No 593->595 596 entropy = 0.0 samples = 6 value = [6, 0] class = No 595->596 597 ASISLEEP <= 7.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 595->597 598 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 597->598 599 entropy = 0.0 samples = 2 value = [2, 0] class = No 597->599 601 HYPEV_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 600->601 604 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 600->604 602 entropy = 0.0 samples = 2 value = [2, 0] class = No 601->602 603 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 601->603 606 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 605->606 607 entropy = 0.0 samples = 4 value = [4, 0] class = No 605->607 609 entropy = 0.0 samples = 17 value = [0, 17] class = Yes 608->609 610 CHPAIN6M_2.0 <= 0.5 entropy = 0.811 samples = 16 value = [4, 12] class = Yes 608->610 611 AHEIGHT <= 65.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 610->611 616 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 610->616 612 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 611->612 613 ADNLONG2_5.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 611->613 614 entropy = 0.0 samples = 4 value = [4, 0] class = No 613->614 615 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 613->615 618 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 617->618 619 entropy = 0.0 samples = 3 value = [3, 0] class = No 617->619 622 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 621->622 623 BMI <= 2861.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 621->623 624 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 623->624 625 ASIRETR_3.0 <= 0.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 623->625 626 entropy = 0.0 samples = 8 value = [8, 0] class = No 625->626 627 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 625->627 630 AHSTATYR_3.0 <= 0.5 entropy = 0.736 samples = 29 value = [6, 23] class = Yes 629->630 641 entropy = 0.0 samples = 22 value = [0, 22] class = Yes 629->641 631 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 630->631 632 AHEIGHT <= 63.5 entropy = 0.9 samples = 19 value = [6, 13] class = Yes 630->632 633 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 632->633 634 AWORPAY_3.0 <= 0.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 632->634 635 ARTH1_2.0 <= 0.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 634->635 640 entropy = 0.0 samples = 4 value = [4, 0] class = No 634->640 636 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 635->636 637 ASISLEEP <= 6.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 635->637 638 entropy = 0.0 samples = 2 value = [2, 0] class = No 637->638 639 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 637->639 643 entropy = 0.0 samples = 1 value = [1, 0] class = No 642->643 644 entropy = 0.0 samples = 19 value = [0, 19] class = Yes 642->644 646 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 645->646 647 ARTH1_2.0 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 645->647 648 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 647->648 649 entropy = 0.0 samples = 7 value = [7, 0] class = No 647->649 651 DBHVWLN_2.0 <= 0.5 entropy = 0.688 samples = 310 value = [57, 253] class = Yes 650->651 750 AHEIGHT <= 73.0 entropy = 0.216 samples = 29 value = [1, 28] class = Yes 650->750 652 PDSICKA_2.0 <= 0.5 entropy = 0.938 samples = 31 value = [11, 20] class = Yes 651->652 665 CHPAIN6M_4.0 <= 0.5 entropy = 0.646 samples = 279 value = [46, 233] class = Yes 651->665 653 CHPAIN6M_2.0 <= 0.5 entropy = 0.995 samples = 24 value = [11, 13] class = Yes 652->653 664 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 652->664 654 BMI <= 3146.5 entropy = 0.722 samples = 10 value = [8, 2] class = No 653->654 659 YRSWRKPA <= 18.5 entropy = 0.75 samples = 14 value = [3, 11] class = Yes 653->659 655 entropy = 0.0 samples = 7 value = [7, 0] class = No 654->655 656 REGION_2 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 654->656 657 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 656->657 658 entropy = 0.0 samples = 1 value = [1, 0] class = No 656->658 660 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 659->660 661 ASIRETR_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 659->661 662 entropy = 0.0 samples = 3 value = [3, 0] class = No 661->662 663 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 661->663 666 DIBREL_2.0 <= 0.5 entropy = 0.682 samples = 249 value = [45, 204] class = Yes 665->666 747 ASICPUSE_3.0 <= 0.5 entropy = 0.211 samples = 30 value = [1, 29] class = Yes 665->747 667 ASISLEEP <= 5.5 entropy = 0.815 samples = 99 value = [25, 74] class = Yes 666->667 706 BMI <= 2882.5 entropy = 0.567 samples = 150 value = [20, 130] class = Yes 666->706 668 SUPERVIS_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 667->668 673 ADNLONG2_1.0 <= 0.5 entropy = 0.755 samples = 92 value = [20, 72] class = Yes 667->673 669 SMKSTAT2_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 668->669 672 entropy = 0.0 samples = 4 value = [4, 0] class = No 668->672 670 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 669->670 671 entropy = 0.0 samples = 1 value = [1, 0] class = No 669->671 674 WRKCATA_4.0 <= 0.5 entropy = 0.267 samples = 22 value = [1, 21] class = Yes 673->674 677 ASIMEDC_3.0 <= 0.5 entropy = 0.844 samples = 70 value = [19, 51] class = Yes 673->677 675 entropy = 0.0 samples = 20 value = [0, 20] class = Yes 674->675 676 entropy = 1.0 samples = 2 value = [1, 1] class = No 674->676 678 YRSWRKPA <= 4.5 entropy = 0.931 samples = 49 value = [17, 32] class = Yes 677->678 701 SPECEQ_2.0 <= 0.5 entropy = 0.454 samples = 21 value = [2, 19] class = Yes 677->701 679 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 678->679 680 LOCALL1B <= 8.5 entropy = 0.974 samples = 42 value = [17, 25] class = Yes 678->680 681 AHEIGHT <= 70.5 entropy = 0.995 samples = 37 value = [17, 20] class = Yes 680->681 700 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 680->700 682 AWEBUSE_2.0 <= 0.5 entropy = 0.977 samples = 34 value = [14, 20] class = Yes 681->682 699 entropy = 0.0 samples = 3 value = [3, 0] class = No 681->699 683 ASISTLV_2.0 <= 0.5 entropy = 0.954 samples = 32 value = [12, 20] class = Yes 682->683 698 entropy = 0.0 samples = 2 value = [2, 0] class = No 682->698 684 LOCALL1B <= 5.5 entropy = 0.999 samples = 23 value = [11, 12] class = Yes 683->684 695 REGION_2 <= 0.5 entropy = 0.503 samples = 9 value = [1, 8] class = Yes 683->695 685 ASICPUSE_2.0 <= 0.5 entropy = 0.918 samples = 18 value = [6, 12] class = Yes 684->685 694 entropy = 0.0 samples = 5 value = [5, 0] class = No 684->694 686 BMI <= 3093.0 entropy = 0.811 samples = 16 value = [4, 12] class = Yes 685->686 693 entropy = 0.0 samples = 2 value = [2, 0] class = No 685->693 687 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 686->687 688 WRKLYR4_2.0 <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 686->688 689 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 688->689 692 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 688->692 690 entropy = 0.0 samples = 4 value = [4, 0] class = No 689->690 691 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 689->691 696 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 695->696 697 entropy = 0.0 samples = 1 value = [1, 0] class = No 695->697 702 WRKLYR4_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 701->702 705 entropy = 0.0 samples = 18 value = [0, 18] class = Yes 701->705 703 entropy = 0.0 samples = 2 value = [2, 0] class = No 702->703 704 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 702->704 707 entropy = 0.0 samples = 22 value = [0, 22] class = Yes 706->707 708 MIEV_2.0 <= 0.5 entropy = 0.625 samples = 128 value = [20, 108] class = Yes 706->708 709 entropy = 0.0 samples = 2 value = [2, 0] class = No 708->709 710 AHEIGHT <= 63.5 entropy = 0.592 samples = 126 value = [18, 108] class = Yes 708->710 711 entropy = 0.0 samples = 15 value = [0, 15] class = Yes 710->711 712 DIBPRE2_2.0 <= 0.5 entropy = 0.639 samples = 111 value = [18, 93] class = Yes 710->712 713 entropy = 0.0 samples = 13 value = [0, 13] class = Yes 712->713 714 WRKCATA_5.0 <= 0.5 entropy = 0.688 samples = 98 value = [18, 80] class = Yes 712->714 715 REGION_4 <= 0.5 entropy = 0.624 samples = 90 value = [14, 76] class = Yes 714->715 742 AHEIGHT <= 69.0 entropy = 1.0 samples = 8 value = [4, 4] class = No 714->742 716 ASISTLV_2.0 <= 0.5 entropy = 0.711 samples = 72 value = [14, 58] class = Yes 715->716 741 entropy = 0.0 samples = 18 value = [0, 18] class = Yes 715->741 717 YRSWRKPA <= 13.5 entropy = 0.835 samples = 49 value = [13, 36] class = Yes 716->717 738 BEDDAYR <= 17.5 entropy = 0.258 samples = 23 value = [1, 22] class = Yes 716->738 718 YTQU_YG1_2.0 <= 0.5 entropy = 0.529 samples = 25 value = [3, 22] class = Yes 717->718 727 BMI <= 3285.5 entropy = 0.98 samples = 24 value = [10, 14] class = Yes 717->727 719 ASICNHC_3.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 718->719 722 BMI <= 3424.0 entropy = 0.267 samples = 22 value = [1, 21] class = Yes 718->722 720 entropy = 0.0 samples = 2 value = [2, 0] class = No 719->720 721 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 719->721 723 entropy = 0.0 samples = 19 value = [0, 19] class = Yes 722->723 724 ALCSTAT_6 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 722->724 725 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 724->725 726 entropy = 0.0 samples = 1 value = [1, 0] class = No 724->726 728 SMKSTAT2_3.0 <= 0.5 entropy = 0.881 samples = 20 value = [6, 14] class = Yes 727->728 737 entropy = 0.0 samples = 4 value = [4, 0] class = No 727->737 729 PAR_STAT_3 <= 0.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 728->729 736 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 728->736 730 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 729->730 731 YRSWRKPA <= 30.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 729->731 732 entropy = 0.0 samples = 5 value = [5, 0] class = No 731->732 733 YRSWRKPA <= 31.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 731->733 734 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 733->734 735 entropy = 0.0 samples = 1 value = [1, 0] class = No 733->735 739 entropy = 0.0 samples = 22 value = [0, 22] class = Yes 738->739 740 entropy = 0.0 samples = 1 value = [1, 0] class = No 738->740 743 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 742->743 744 YRSWRKPA <= 23.0 entropy = 0.722 samples = 5 value = [4, 1] class = No 742->744 745 entropy = 0.0 samples = 4 value = [4, 0] class = No 744->745 746 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 744->746 748 entropy = 0.0 samples = 28 value = [0, 28] class = Yes 747->748 749 entropy = 1.0 samples = 2 value = [1, 1] class = No 747->749 751 entropy = 0.0 samples = 26 value = [0, 26] class = Yes 750->751 752 AWORPAY_3.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 750->752 753 entropy = 0.0 samples = 1 value = [1, 0] class = No 752->753 754 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 752->754 757 DBHVCLN_2.0 <= 0.5 entropy = 0.999 samples = 52 value = [25, 27] class = Yes 756->757 778 ALCSTAT_5 <= 0.5 entropy = 0.848 samples = 291 value = [80, 211] class = Yes 756->778 758 CHDEV_2.0 <= 0.5 entropy = 0.918 samples = 27 value = [18, 9] class = No 757->758 769 BMI <= 2891.5 entropy = 0.855 samples = 25 value = [7, 18] class = Yes 757->769 759 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 758->759 760 LOCALL1B <= 6.5 entropy = 0.811 samples = 24 value = [18, 6] class = No 758->760 761 HIT3A_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [8, 6] class = No 760->761 768 entropy = 0.0 samples = 10 value = [10, 0] class = No 760->768 762 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 761->762 763 R_MARITL_3 <= 0.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 761->763 764 ALCSTAT_5 <= 0.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 763->764 767 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 763->767 765 entropy = 0.0 samples = 8 value = [8, 0] class = No 764->765 766 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 764->766 770 ALCSTAT_2 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 769->770 773 HYBPLEV_2.0 <= 0.5 entropy = 0.61 samples = 20 value = [3, 17] class = Yes 769->773 771 entropy = 0.0 samples = 4 value = [4, 0] class = No 770->771 772 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 770->772 774 VIM_GLEV_2.0 <= 0.5 entropy = 0.31 samples = 18 value = [1, 17] class = Yes 773->774 777 entropy = 0.0 samples = 2 value = [2, 0] class = No 773->777 775 entropy = 0.0 samples = 1 value = [1, 0] class = No 774->775 776 entropy = 0.0 samples = 17 value = [0, 17] class = Yes 774->776 779 ASIMEDC_2.0 <= 0.5 entropy = 0.886 samples = 247 value = [75, 172] class = Yes 778->779 874 AHEIGHT <= 62.5 entropy = 0.511 samples = 44 value = [5, 39] class = Yes 778->874 780 PAR_STAT_2 <= 0.5 entropy = 0.943 samples = 172 value = [62, 110] class = Yes 779->780 853 BMI <= 3478.0 entropy = 0.665 samples = 75 value = [13, 62] class = Yes 779->853 781 LOCALL1B <= 7.5 entropy = 0.93 samples = 168 value = [58, 110] class = Yes 780->781 852 entropy = 0.0 samples = 4 value = [4, 0] class = No 780->852 782 AHAYFYR_2.0 <= 0.5 entropy = 0.968 samples = 129 value = [51, 78] class = Yes 781->782 841 ASIRETR_4.0 <= 0.5 entropy = 0.679 samples = 39 value = [7, 32] class = Yes 781->841 783 SUPERVIS_2.0 <= 0.5 entropy = 0.837 samples = 15 value = [11, 4] class = No 782->783 788 AMIGR_2.0 <= 0.5 entropy = 0.935 samples = 114 value = [40, 74] class = Yes 782->788 784 REGION_3 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 783->784 787 entropy = 0.0 samples = 9 value = [9, 0] class = No 783->787 785 entropy = 0.0 samples = 2 value = [2, 0] class = No 784->785 786 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 784->786 789 CHPAIN6M_3.0 <= 0.5 entropy = 0.485 samples = 19 value = [2, 17] class = Yes 788->789 794 BEDDAYR <= 143.0 entropy = 0.971 samples = 95 value = [38, 57] class = Yes 788->794 790 entropy = 0.0 samples = 15 value = [0, 15] class = Yes 789->790 791 ALCSTAT_6 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 789->791 792 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 791->792 793 entropy = 0.0 samples = 2 value = [2, 0] class = No 791->793 795 HIT1A_2.0 <= 0.5 entropy = 0.958 samples = 92 value = [35, 57] class = Yes 794->795 840 entropy = 0.0 samples = 3 value = [3, 0] class = No 794->840 796 HIT3A_2.0 <= 0.5 entropy = 0.811 samples = 44 value = [11, 33] class = Yes 795->796 813 BMI <= 2882.5 entropy = 1.0 samples = 48 value = [24, 24] class = No 795->813 797 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 796->797 798 VIMGLASS_2.0 <= 0.5 entropy = 0.898 samples = 35 value = [11, 24] class = Yes 796->798 799 YRSWRKPA <= 12.5 entropy = 0.722 samples = 25 value = [5, 20] class = Yes 798->799 808 CHLEV_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 798->808 800 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 799->800 801 WRKLYR4_2.0 <= 0.5 entropy = 0.94 samples = 14 value = [5, 9] class = Yes 799->801 802 JNTSYMP_2.0 <= 0.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 801->802 807 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 801->807 803 entropy = 0.0 samples = 4 value = [4, 0] class = No 802->803 804 SINYR_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 802->804 805 entropy = 0.0 samples = 1 value = [1, 0] class = No 804->805 806 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 804->806 809 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 808->809 810 PAINECK_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 808->810 811 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 810->811 812 entropy = 0.0 samples = 6 value = [6, 0] class = No 810->812 814 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 813->814 815 BMI <= 3387.0 entropy = 0.994 samples = 44 value = [24, 20] class = No 813->815 816 BMI <= 3283.5 entropy = 0.971 samples = 40 value = [24, 16] class = No 815->816 839 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 815->839 817 BMI <= 2955.0 entropy = 0.995 samples = 35 value = [19, 16] class = No 816->817 838 entropy = 0.0 samples = 5 value = [5, 0] class = No 816->838 818 entropy = 0.0 samples = 4 value = [4, 0] class = No 817->818 819 ASIRETR_2.0 <= 0.5 entropy = 0.999 samples = 31 value = [15, 16] class = Yes 817->819 820 BMI <= 3248.5 entropy = 0.985 samples = 28 value = [12, 16] class = Yes 819->820 837 entropy = 0.0 samples = 3 value = [3, 0] class = No 819->837 821 HYBPLEV_5.0 <= 0.5 entropy = 0.999 samples = 23 value = [12, 11] class = No 820->821 836 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 820->836 822 REGION_3 <= 0.5 entropy = 0.985 samples = 21 value = [12, 9] class = No 821->822 835 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 821->835 823 BEDDAYR <= 1.0 entropy = 0.985 samples = 14 value = [6, 8] class = Yes 822->823 832 SPECEQ_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 822->832 824 DIBREL_2.0 <= 0.5 entropy = 0.994 samples = 11 value = [6, 5] class = No 823->824 831 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 823->831 825 entropy = 0.0 samples = 3 value = [3, 0] class = No 824->825 826 APLKIND_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 824->826 827 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 826->827 828 VIM_MDEV_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 826->828 829 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 828->829 830 entropy = 0.0 samples = 3 value = [3, 0] class = No 828->830 833 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 832->833 834 entropy = 0.0 samples = 6 value = [6, 0] class = No 832->834 842 AHEIGHT <= 71.5 entropy = 0.937 samples = 17 value = [6, 11] class = Yes 841->842 849 AHEIGHT <= 61.5 entropy = 0.267 samples = 22 value = [1, 21] class = Yes 841->849 843 STREV_2.0 <= 0.5 entropy = 0.75 samples = 14 value = [3, 11] class = Yes 842->843 848 entropy = 0.0 samples = 3 value = [3, 0] class = No 842->848 844 entropy = 0.0 samples = 2 value = [2, 0] class = No 843->844 845 AMIGR_2.0 <= 0.5 entropy = 0.414 samples = 12 value = [1, 11] class = Yes 843->845 846 entropy = 1.0 samples = 2 value = [1, 1] class = No 845->846 847 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 845->847 850 entropy = 0.0 samples = 1 value = [1, 0] class = No 849->850 851 entropy = 0.0 samples = 21 value = [0, 21] class = Yes 849->851 854 YRSWRKPA <= 4.5 entropy = 0.612 samples = 73 value = [11, 62] class = Yes 853->854 873 entropy = 0.0 samples = 2 value = [2, 0] class = No 853->873 855 ULCEV_2.0 <= 0.5 entropy = 0.934 samples = 20 value = [7, 13] class = Yes 854->855 864 WRKCATA_5.0 <= 0.5 entropy = 0.386 samples = 53 value = [4, 49] class = Yes 854->864 856 entropy = 0.0 samples = 4 value = [4, 0] class = No 855->856 857 YRSWRKPA <= 2.5 entropy = 0.696 samples = 16 value = [3, 13] class = Yes 855->857 858 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 857->858 859 AHSTATYR_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 857->859 860 entropy = 0.0 samples = 2 value = [2, 0] class = No 859->860 861 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 859->861 862 entropy = 0.0 samples = 1 value = [1, 0] class = No 861->862 863 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 861->863 865 AMDLONGR_3.0 <= 0.5 entropy = 0.246 samples = 49 value = [2, 47] class = Yes 864->865 870 ALCSTAT_8 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 864->870 866 BMI <= 2828.0 entropy = 0.146 samples = 48 value = [1, 47] class = Yes 865->866 869 entropy = 0.0 samples = 1 value = [1, 0] class = No 865->869 867 entropy = 1.0 samples = 2 value = [1, 1] class = No 866->867 868 entropy = 0.0 samples = 46 value = [0, 46] class = Yes 866->868 871 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 870->871 872 entropy = 0.0 samples = 2 value = [2, 0] class = No 870->872 875 PAR_STAT_3 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 874->875 880 VIMGLASS_2.0 <= 0.5 entropy = 0.297 samples = 38 value = [2, 36] class = Yes 874->880 876 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 875->876 877 BMI <= 3097.0 entropy = 0.811 samples = 4 value = [3, 1] class = No 875->877 878 entropy = 0.0 samples = 3 value = [3, 0] class = No 877->878 879 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 877->879 881 entropy = 0.0 samples = 32 value = [0, 32] class = Yes 880->881 882 AHEARST1_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 880->882 883 SUPERVIS_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 882->883 886 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 882->886 884 entropy = 0.0 samples = 2 value = [2, 0] class = No 883->884 885 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 883->885 888 ASICPUSE_4.0 <= 0.5 entropy = 0.6 samples = 356 value = [52, 304] class = Yes 887->888 983 entropy = 0.0 samples = 25 value = [0, 25] class = Yes 887->983 889 CIGAREV2_2.0 <= 0.5 entropy = 0.746 samples = 127 value = [27, 100] class = Yes 888->889 930 BMI <= 3618.5 entropy = 0.497 samples = 229 value = [25, 204] class = Yes 888->930 890 ASIMEDC_3.0 <= 0.5 entropy = 0.362 samples = 29 value = [2, 27] class = Yes 889->890 895 AHCNOYR2 <= 0.5 entropy = 0.819 samples = 98 value = [25, 73] class = Yes 889->895 891 entropy = 0.0 samples = 22 value = [0, 22] class = Yes 890->891 892 DOINGLWA_5.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 890->892 893 entropy = 0.0 samples = 2 value = [2, 0] class = No 892->893 894 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 892->894 896 entropy = 0.0 samples = 2 value = [2, 0] class = No 895->896 897 BMI <= 4133.0 entropy = 0.794 samples = 96 value = [23, 73] class = Yes 895->897 898 HYBPLEV_2.0 <= 0.5 entropy = 0.863 samples = 77 value = [22, 55] class = Yes 897->898 927 WRKCATA_5.0 <= 0.5 entropy = 0.297 samples = 19 value = [1, 18] class = Yes 897->927 899 AHCNOYR2 <= 4.5 entropy = 0.771 samples = 62 value = [14, 48] class = Yes 898->899 922 YRSWRKPA <= 7.5 entropy = 0.997 samples = 15 value = [8, 7] class = No 898->922 900 REGION_4 <= 0.5 entropy = 0.855 samples = 50 value = [14, 36] class = Yes 899->900 921 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 899->921 901 ALCSTAT_7 <= 0.5 entropy = 0.722 samples = 40 value = [8, 32] class = Yes 900->901 916 DBHVCLN_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 900->916 902 ASISLEEP <= 6.5 entropy = 0.629 samples = 38 value = [6, 32] class = Yes 901->902 915 entropy = 0.0 samples = 2 value = [2, 0] class = No 901->915 903 entropy = 0.0 samples = 14 value = [0, 14] class = Yes 902->903 904 ASRGYR_2.0 <= 0.5 entropy = 0.811 samples = 24 value = [6, 18] class = Yes 902->904 905 entropy = 0.0 samples = 2 value = [2, 0] class = No 904->905 906 AHEIGHT <= 65.0 entropy = 0.684 samples = 22 value = [4, 18] class = Yes 904->906 907 AHCNOYR2 <= 1.5 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 906->907 914 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 906->914 908 entropy = 0.0 samples = 2 value = [2, 0] class = No 907->908 909 WRKLYR4_2.0 <= 0.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 907->909 910 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 909->910 913 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 909->913 911 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 910->911 912 entropy = 0.0 samples = 2 value = [2, 0] class = No 910->912 917 HYBPLEV_3.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 916->917 920 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 916->920 918 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 917->918 919 entropy = 0.0 samples = 6 value = [6, 0] class = No 917->919 923 entropy = 0.0 samples = 5 value = [5, 0] class = No 922->923 924 SMKSTAT2_4.0 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 922->924 925 entropy = 0.0 samples = 3 value = [3, 0] class = No 924->925 926 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 924->926 928 entropy = 0.0 samples = 18 value = [0, 18] class = Yes 927->928 929 entropy = 0.0 samples = 1 value = [1, 0] class = No 927->929 931 HYBPLEV_5.0 <= 0.5 entropy = 0.139 samples = 51 value = [1, 50] class = Yes 930->931 936 AHSTATYR_2.0 <= 0.5 entropy = 0.571 samples = 178 value = [24, 154] class = Yes 930->936 932 entropy = 0.0 samples = 47 value = [0, 47] class = Yes 931->932 933 BMI <= 3580.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 931->933 934 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 933->934 935 entropy = 0.0 samples = 1 value = [1, 0] class = No 933->935 937 YRSWRKPA <= 6.5 entropy = 0.627 samples = 153 value = [24, 129] class = Yes 936->937 982 entropy = 0.0 samples = 25 value = [0, 25] class = Yes 936->982 938 LOCALL1B <= 5.5 entropy = 0.395 samples = 77 value = [6, 71] class = Yes 937->938 953 AHEARST1_2.0 <= 0.5 entropy = 0.79 samples = 76 value = [18, 58] class = Yes 937->953 939 AHAYFYR_2.0 <= 0.5 entropy = 0.135 samples = 53 value = [1, 52] class = Yes 938->939 944 PAINFACE_2.0 <= 0.5 entropy = 0.738 samples = 24 value = [5, 19] class = Yes 938->944 940 CHPAIN6M_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 939->940 943 entropy = 0.0 samples = 48 value = [0, 48] class = Yes 939->943 941 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 940->941 942 entropy = 0.0 samples = 1 value = [1, 0] class = No 940->942 945 AHEIGHT <= 67.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 944->945 948 AHEIGHT <= 71.5 entropy = 0.469 samples = 20 value = [2, 18] class = Yes 944->948 946 entropy = 0.0 samples = 3 value = [3, 0] class = No 945->946 947 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 945->947 949 entropy = 0.0 samples = 16 value = [0, 16] class = Yes 948->949 950 ASISTLV_3.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 948->950 951 entropy = 0.0 samples = 2 value = [2, 0] class = No 950->951 952 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 950->952 954 BMI <= 3664.5 entropy = 0.918 samples = 45 value = [15, 30] class = Yes 953->954 975 ARTH1_2.0 <= 0.5 entropy = 0.459 samples = 31 value = [3, 28] class = Yes 953->975 955 entropy = 0.0 samples = 3 value = [3, 0] class = No 954->955 956 FLA1AR_2 <= 0.5 entropy = 0.863 samples = 42 value = [12, 30] class = Yes 954->956 957 ALC1YR_2.0 <= 0.5 entropy = 0.559 samples = 23 value = [3, 20] class = Yes 956->957 964 CHPAIN6M_2.0 <= 0.5 entropy = 0.998 samples = 19 value = [9, 10] class = Yes 956->964 958 entropy = 0.0 samples = 16 value = [0, 16] class = Yes 957->958 959 SPECEQ_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 957->959 960 entropy = 0.0 samples = 2 value = [2, 0] class = No 959->960 961 ASIRETR_3.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 959->961 962 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 961->962 963 entropy = 0.0 samples = 1 value = [1, 0] class = No 961->963 965 VIMGLASS_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 964->965 968 BMI <= 4005.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 964->968 966 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 965->966 967 entropy = 0.0 samples = 1 value = [1, 0] class = No 965->967 969 entropy = 0.0 samples = 5 value = [5, 0] class = No 968->969 970 REGION_3 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 968->970 971 SMKSTAT2_4.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 970->971 974 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 970->974 972 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 971->972 973 entropy = 0.0 samples = 3 value = [3, 0] class = No 971->973 976 REGION_2 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 975->976 981 entropy = 0.0 samples = 21 value = [0, 21] class = Yes 975->981 977 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 976->977 978 ACOLD2W_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 976->978 979 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 978->979 980 entropy = 0.0 samples = 3 value = [3, 0] class = No 978->980 985 DBHVPAN_2.0 <= 0.5 entropy = 0.853 samples = 3355 value = [2422, 933] class = No 984->985 2084 DBHVPAN_2.0 <= 0.5 entropy = 0.559 samples = 6187 value = [5380, 807] class = No 984->2084 986 BEDDAYR <= 3.5 entropy = 0.927 samples = 1734 value = [1141, 593] class = No 985->986 1611 DBHVCLN_2.0 <= 0.5 entropy = 0.741 samples = 1621 value = [1281, 340] class = No 985->1611 987 HYPEV_2.0 <= 0.5 entropy = 0.883 samples = 1372 value = [959, 413] class = No 986->987 1476 AHCNOYR2 <= 2.5 entropy = 1.0 samples = 362 value = [182, 180] class = No 986->1476 988 AHCNOYR2 <= 1.5 entropy = 0.957 samples = 605 value = [376, 229] class = No 987->988 1241 AHCNOYR2 <= 0.5 entropy = 0.795 samples = 767 value = [583, 184] class = No 987->1241 989 BMI <= 3015.5 entropy = 0.762 samples = 86 value = [67, 19] class = No 988->989 1018 AWEBUSE_2.0 <= 0.5 entropy = 0.974 samples = 519 value = [309, 210] class = No 988->1018 990 SEX_2 <= 0.5 entropy = 0.561 samples = 61 value = [53, 8] class = No 989->990 1007 YRSWRKPA <= 2.5 entropy = 0.99 samples = 25 value = [14, 11] class = No 989->1007 991 HYBPLEV_5.0 <= 0.5 entropy = 0.201 samples = 32 value = [31, 1] class = No 990->991 996 BMI <= 2618.5 entropy = 0.797 samples = 29 value = [22, 7] class = No 990->996 992 entropy = 0.0 samples = 28 value = [28, 0] class = No 991->992 993 AHEARST1_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 991->993 994 entropy = 0.0 samples = 3 value = [3, 0] class = No 993->994 995 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 993->995 997 ADNLONG2_2.0 <= 0.5 entropy = 0.971 samples = 15 value = [9, 6] class = No 996->997 1004 AMIGR_2.0 <= 0.5 entropy = 0.371 samples = 14 value = [13, 1] class = No 996->1004 998 YRSWRKPA <= 26.0 entropy = 0.811 samples = 12 value = [9, 3] class = No 997->998 1003 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 997->1003 999 VIM_MDEV_2.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 998->999 1002 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 998->1002 1000 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 999->1000 1001 entropy = 0.0 samples = 9 value = [9, 0] class = No 999->1001 1005 entropy = 1.0 samples = 2 value = [1, 1] class = No 1004->1005 1006 entropy = 0.0 samples = 12 value = [12, 0] class = No 1004->1006 1008 R_MARITL_2 <= 0.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 1007->1008 1011 LOCALL1B <= 4.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 1007->1011 1009 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1008->1009 1010 entropy = 0.0 samples = 2 value = [2, 0] class = No 1008->1010 1012 DIBREL_2.0 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 1011->1012 1017 entropy = 0.0 samples = 8 value = [8, 0] class = No 1011->1017 1013 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1012->1013 1014 BMI <= 3254.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1012->1014 1015 entropy = 0.0 samples = 4 value = [4, 0] class = No 1014->1015 1016 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1014->1016 1019 ASISTLV_3.0 <= 0.5 entropy = 0.991 samples = 369 value = [205, 164] class = No 1018->1019 1180 ADNLONG2_3.0 <= 0.5 entropy = 0.889 samples = 150 value = [104, 46] class = No 1018->1180 1020 YRSWRKPA <= 19.5 entropy = 0.999 samples = 268 value = [138, 130] class = No 1019->1020 1139 LOCALL1B <= 7.5 entropy = 0.922 samples = 101 value = [67, 34] class = No 1019->1139 1021 DIBPRE2_2.0 <= 0.5 entropy = 0.994 samples = 171 value = [78, 93] class = Yes 1020->1021 1092 HIT2A_2.0 <= 0.5 entropy = 0.959 samples = 97 value = [60, 37] class = No 1020->1092 1022 YRSWRKPA <= 3.5 entropy = 0.773 samples = 22 value = [5, 17] class = Yes 1021->1022 1029 ASISLEEP <= 4.5 entropy = 1.0 samples = 149 value = [73, 76] class = Yes 1021->1029 1023 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 1022->1023 1024 ADNLONG2_1.0 <= 0.5 entropy = 0.98 samples = 12 value = [5, 7] class = Yes 1022->1024 1025 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1024->1025 1026 AINTIL2W_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 1024->1026 1027 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1026->1027 1028 entropy = 0.0 samples = 5 value = [5, 0] class = No 1026->1028 1030 entropy = 0.0 samples = 6 value = [6, 0] class = No 1029->1030 1031 BMI <= 2275.0 entropy = 0.997 samples = 143 value = [67, 76] class = Yes 1029->1031 1032 AHAYFYR_2.0 <= 0.5 entropy = 0.887 samples = 23 value = [16, 7] class = No 1031->1032 1043 WRKLYR4_1.0 <= 0.5 entropy = 0.984 samples = 120 value = [51, 69] class = Yes 1031->1043 1033 entropy = 0.0 samples = 6 value = [6, 0] class = No 1032->1033 1034 HIT3A_2.0 <= 0.5 entropy = 0.977 samples = 17 value = [10, 7] class = No 1032->1034 1035 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1034->1035 1036 AHEARST1_3.0 <= 0.5 entropy = 0.863 samples = 14 value = [10, 4] class = No 1034->1036 1037 AHEARST1_4.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 1036->1037 1040 PDSICKA_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1036->1040 1038 entropy = 0.0 samples = 9 value = [9, 0] class = No 1037->1038 1039 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1037->1039 1041 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1040->1041 1042 entropy = 0.0 samples = 1 value = [1, 0] class = No 1040->1042 1044 ARTH1_2.0 <= 0.5 entropy = 0.992 samples = 114 value = [51, 63] class = Yes 1043->1044 1091 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1043->1091 1045 DIBREL_2.0 <= 0.5 entropy = 0.933 samples = 63 value = [22, 41] class = Yes 1044->1045 1068 LOCALL1B <= 3.5 entropy = 0.986 samples = 51 value = [29, 22] class = No 1044->1068 1046 REGION_4 <= 0.5 entropy = 0.999 samples = 29 value = [15, 14] class = No 1045->1046 1057 SEX_2 <= 0.5 entropy = 0.734 samples = 34 value = [7, 27] class = Yes 1045->1057 1047 CBRCHYR_2.0 <= 0.5 entropy = 0.99 samples = 25 value = [11, 14] class = Yes 1046->1047 1056 entropy = 0.0 samples = 4 value = [4, 0] class = No 1046->1056 1048 entropy = 0.0 samples = 3 value = [3, 0] class = No 1047->1048 1049 YRSWRKPA <= 15.5 entropy = 0.946 samples = 22 value = [8, 14] class = Yes 1047->1049 1050 LOCALL1B <= 3.5 entropy = 0.831 samples = 19 value = [5, 14] class = Yes 1049->1050 1055 entropy = 0.0 samples = 3 value = [3, 0] class = No 1049->1055 1051 AHCNOYR2 <= 4.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 1050->1051 1054 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 1050->1054 1052 entropy = 0.0 samples = 5 value = [5, 0] class = No 1051->1052 1053 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1051->1053 1058 YRSWRKPA <= 9.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 1057->1058 1063 YRSWRKPA <= 13.0 entropy = 0.402 samples = 25 value = [2, 23] class = Yes 1057->1063 1059 entropy = 0.0 samples = 4 value = [4, 0] class = No 1058->1059 1060 VIMGLASS_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1058->1060 1061 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1060->1061 1062 entropy = 0.0 samples = 1 value = [1, 0] class = No 1060->1062 1064 entropy = 0.0 samples = 19 value = [0, 19] class = Yes 1063->1064 1065 REGION_2 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 1063->1065 1066 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1065->1066 1067 entropy = 0.0 samples = 2 value = [2, 0] class = No 1065->1067 1069 HIT1A_2.0 <= 0.5 entropy = 0.619 samples = 13 value = [11, 2] class = No 1068->1069 1072 AHEARST1_3.0 <= 0.5 entropy = 0.998 samples = 38 value = [18, 20] class = Yes 1068->1072 1070 entropy = 0.0 samples = 11 value = [11, 0] class = No 1069->1070 1071 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1069->1071 1073 R_MARITL_3 <= 0.5 entropy = 0.974 samples = 32 value = [13, 19] class = Yes 1072->1073 1088 ALCSTAT_7 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 1072->1088 1074 CLCKTP <= 3.5 entropy = 1.0 samples = 26 value = [13, 13] class = No 1073->1074 1087 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1073->1087 1075 CIGAREV2_2.0 <= 0.5 entropy = 0.896 samples = 16 value = [11, 5] class = No 1074->1075 1082 ASISLEEP <= 6.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 1074->1082 1076 entropy = 0.0 samples = 7 value = [7, 0] class = No 1075->1076 1077 SMKSTAT2_4.0 <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 1075->1077 1078 CHPAIN6M_3.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 1077->1078 1081 entropy = 0.0 samples = 3 value = [3, 0] class = No 1077->1081 1079 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1078->1079 1080 entropy = 0.0 samples = 1 value = [1, 0] class = No 1078->1080 1083 entropy = 0.0 samples = 1 value = [1, 0] class = No 1082->1083 1084 AASMEV_2.0 <= 0.5 entropy = 0.503 samples = 9 value = [1, 8] class = Yes 1082->1084 1085 entropy = 0.0 samples = 1 value = [1, 0] class = No 1084->1085 1086 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 1084->1086 1089 entropy = 0.0 samples = 5 value = [5, 0] class = No 1088->1089 1090 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1088->1090 1093 YRSWRKPA <= 21.5 entropy = 0.949 samples = 19 value = [7, 12] class = Yes 1092->1093 1104 BMI <= 3110.0 entropy = 0.905 samples = 78 value = [53, 25] class = No 1092->1104 1094 entropy = 0.0 samples = 2 value = [2, 0] class = No 1093->1094 1095 BEDDAYR <= 1.5 entropy = 0.874 samples = 17 value = [5, 12] class = Yes 1093->1095 1096 CHLEV_2.0 <= 0.5 entropy = 0.722 samples = 15 value = [3, 12] class = Yes 1095->1096 1103 entropy = 0.0 samples = 2 value = [2, 0] class = No 1095->1103 1097 AHEIGHT <= 67.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 1096->1097 1102 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 1096->1102 1098 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1097->1098 1099 AMIGR_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1097->1099 1100 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1099->1100 1101 entropy = 0.0 samples = 3 value = [3, 0] class = No 1099->1101 1105 WRKCATA_3.0 <= 0.5 entropy = 0.792 samples = 63 value = [48, 15] class = No 1104->1105 1130 SEX_2 <= 0.5 entropy = 0.918 samples = 15 value = [5, 10] class = Yes 1104->1130 1106 CANEV_2.0 <= 0.5 entropy = 0.665 samples = 52 value = [43, 9] class = No 1105->1106 1123 AHEARST1_2.0 <= 0.5 entropy = 0.994 samples = 11 value = [5, 6] class = Yes 1105->1123 1107 entropy = 0.0 samples = 19 value = [19, 0] class = No 1106->1107 1108 WRKCATA_2.0 <= 0.5 entropy = 0.845 samples = 33 value = [24, 9] class = No 1106->1108 1109 AHCNOYR2 <= 4.5 entropy = 0.736 samples = 29 value = [23, 6] class = No 1108->1109 1120 YRSWRKPA <= 23.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1108->1120 1110 AHEIGHT <= 73.5 entropy = 0.31 samples = 18 value = [17, 1] class = No 1109->1110 1113 HIT1A_2.0 <= 0.5 entropy = 0.994 samples = 11 value = [6, 5] class = No 1109->1113 1111 entropy = 0.0 samples = 16 value = [16, 0] class = No 1110->1111 1112 entropy = 1.0 samples = 2 value = [1, 1] class = No 1110->1112 1114 AHEARST1_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 1113->1114 1119 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1113->1119 1115 entropy = 0.0 samples = 5 value = [5, 0] class = No 1114->1115 1116 BMI <= 2390.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1114->1116 1117 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1116->1117 1118 entropy = 0.0 samples = 1 value = [1, 0] class = No 1116->1118 1121 entropy = 0.0 samples = 1 value = [1, 0] class = No 1120->1121 1122 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1120->1122 1124 R_MARITL_2 <= 0.5 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 1123->1124 1129 entropy = 0.0 samples = 3 value = [3, 0] class = No 1123->1129 1125 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1124->1125 1126 DBHVCLN_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1124->1126 1127 entropy = 0.0 samples = 2 value = [2, 0] class = No 1126->1127 1128 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1126->1128 1131 VIM_MDEV_2.0 <= 0.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 1130->1131 1138 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1130->1138 1132 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1131->1132 1133 JNTSYMP_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 1131->1133 1134 entropy = 0.0 samples = 4 value = [4, 0] class = No 1133->1134 1135 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1133->1135 1136 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1135->1136 1137 entropy = 0.0 samples = 1 value = [1, 0] class = No 1135->1137 1140 FLUVACYR_2.0 <= 0.5 entropy = 0.962 samples = 83 value = [51, 32] class = No 1139->1140 1175 HIT3A_2.0 <= 0.5 entropy = 0.503 samples = 18 value = [16, 2] class = No 1139->1175 1141 YRSWRKPA <= 4.5 entropy = 1.0 samples = 49 value = [25, 24] class = No 1140->1141 1164 ASICPUSE_2.0 <= 0.5 entropy = 0.787 samples = 34 value = [26, 8] class = No 1140->1164 1142 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1141->1142 1143 REGION_3 <= 0.5 entropy = 0.974 samples = 42 value = [25, 17] class = No 1141->1143 1144 CLCKTP <= 3.5 entropy = 0.996 samples = 28 value = [13, 15] class = Yes 1143->1144 1159 CIGAREV2_2.0 <= 0.5 entropy = 0.592 samples = 14 value = [12, 2] class = No 1143->1159 1145 PAINLB_2.0 <= 0.5 entropy = 0.995 samples = 24 value = [13, 11] class = No 1144->1145 1158 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1144->1158 1146 ASIMEDC_2.0 <= 0.5 entropy = 0.863 samples = 14 value = [10, 4] class = No 1145->1146 1153 ALCSTAT_6 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 1145->1153 1147 ARTH1_2.0 <= 0.5 entropy = 0.65 samples = 12 value = [10, 2] class = No 1146->1147 1152 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1146->1152 1148 entropy = 0.0 samples = 8 value = [8, 0] class = No 1147->1148 1149 ALCSTAT_5 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1147->1149 1150 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1149->1150 1151 entropy = 0.0 samples = 2 value = [2, 0] class = No 1149->1151 1154 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1153->1154 1155 ADNLONG2_1.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1153->1155 1156 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1155->1156 1157 entropy = 0.0 samples = 3 value = [3, 0] class = No 1155->1157 1160 ASICNHC_3.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1159->1160 1163 entropy = 0.0 samples = 11 value = [11, 0] class = No 1159->1163 1161 entropy = 0.0 samples = 1 value = [1, 0] class = No 1160->1161 1162 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1160->1162 1165 HIT2A_2.0 <= 0.5 entropy = 0.592 samples = 28 value = [24, 4] class = No 1164->1165 1172 LOCALL1B <= 2.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 1164->1172 1166 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1165->1166 1167 AHEARST1_3.0 <= 0.5 entropy = 0.391 samples = 26 value = [24, 2] class = No 1165->1167 1168 APLKIND_2.0 <= 0.5 entropy = 0.242 samples = 25 value = [24, 1] class = No 1167->1168 1171 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1167->1171 1169 entropy = 1.0 samples = 2 value = [1, 1] class = No 1168->1169 1170 entropy = 0.0 samples = 23 value = [23, 0] class = No 1168->1170 1173 entropy = 0.0 samples = 2 value = [2, 0] class = No 1172->1173 1174 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1172->1174 1176 AHEIGHT <= 68.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1175->1176 1179 entropy = 0.0 samples = 14 value = [14, 0] class = No 1175->1179 1177 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1176->1177 1178 entropy = 0.0 samples = 2 value = [2, 0] class = No 1176->1178 1181 ASIRETR_2.0 <= 0.5 entropy = 0.926 samples = 129 value = [85, 44] class = No 1180->1181 1236 HIT1A_2.0 <= 0.5 entropy = 0.454 samples = 21 value = [19, 2] class = No 1180->1236 1182 STREV_2.0 <= 0.5 entropy = 0.878 samples = 111 value = [78, 33] class = No 1181->1182 1229 BMI <= 2974.0 entropy = 0.964 samples = 18 value = [7, 11] class = Yes 1181->1229 1183 ADNLONG2_1.0 <= 0.5 entropy = 0.918 samples = 12 value = [4, 8] class = Yes 1182->1183 1188 LOCALL1B <= 8.5 entropy = 0.815 samples = 99 value = [74, 25] class = No 1182->1188 1184 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1183->1184 1185 AVISACT_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1183->1185 1186 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1185->1186 1187 entropy = 0.0 samples = 4 value = [4, 0] class = No 1185->1187 1189 CLCKTP <= 1.5 entropy = 0.736 samples = 87 value = [69, 18] class = No 1188->1189 1222 YRSWRKPA <= 26.0 entropy = 0.98 samples = 12 value = [5, 7] class = Yes 1188->1222 1190 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1189->1190 1191 AHEARST1_5.0 <= 0.5 entropy = 0.698 samples = 85 value = [69, 16] class = No 1189->1191 1192 ADNLONG2_5.0 <= 0.5 entropy = 0.601 samples = 75 value = [64, 11] class = No 1191->1192 1215 ASISLEEP <= 8.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 1191->1215 1193 BEDDAYR <= 0.5 entropy = 0.694 samples = 59 value = [48, 11] class = No 1192->1193 1214 entropy = 0.0 samples = 16 value = [16, 0] class = No 1192->1214 1194 APLKIND_2.0 <= 0.5 entropy = 0.577 samples = 51 value = [44, 7] class = No 1193->1194 1211 YRSWRKPA <= 16.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 1193->1211 1195 entropy = 0.0 samples = 14 value = [14, 0] class = No 1194->1195 1196 WRKCATA_5.0 <= 0.5 entropy = 0.7 samples = 37 value = [30, 7] class = No 1194->1196 1197 AHAYFYR_2.0 <= 0.5 entropy = 0.592 samples = 35 value = [30, 5] class = No 1196->1197 1210 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1196->1210 1198 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1197->1198 1199 BMI <= 2734.5 entropy = 0.523 samples = 34 value = [30, 4] class = No 1197->1199 1200 entropy = 0.0 samples = 18 value = [18, 0] class = No 1199->1200 1201 DIBREL_2.0 <= 0.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 1199->1201 1202 entropy = 0.0 samples = 6 value = [6, 0] class = No 1201->1202 1203 AWORPAY_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 1201->1203 1204 AHEARST1_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 1203->1204 1209 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1203->1209 1205 entropy = 0.0 samples = 5 value = [5, 0] class = No 1204->1205 1206 ASIMEDC_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1204->1206 1207 entropy = 0.0 samples = 1 value = [1, 0] class = No 1206->1207 1208 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1206->1208 1212 entropy = 0.0 samples = 4 value = [4, 0] class = No 1211->1212 1213 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1211->1213 1216 DIBREL_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 1215->1216 1221 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1215->1221 1217 LOCALL1B <= 4.0 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1216->1217 1220 entropy = 0.0 samples = 4 value = [4, 0] class = No 1216->1220 1218 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1217->1218 1219 entropy = 0.0 samples = 1 value = [1, 0] class = No 1217->1219 1223 SEX_2 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 1222->1223 1228 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1222->1228 1224 ADNLONG2_5.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1223->1224 1227 entropy = 0.0 samples = 4 value = [4, 0] class = No 1223->1227 1225 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1224->1225 1226 entropy = 0.0 samples = 1 value = [1, 0] class = No 1224->1226 1230 BMI <= 2724.5 entropy = 0.98 samples = 12 value = [7, 5] class = No 1229->1230 1235 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1229->1235 1231 YRSWRKPA <= 25.0 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 1230->1231 1234 entropy = 0.0 samples = 6 value = [6, 0] class = No 1230->1234 1232 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1231->1232 1233 entropy = 0.0 samples = 1 value = [1, 0] class = No 1231->1233 1237 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1236->1237 1238 AHEARST1_5.0 <= 0.5 entropy = 0.286 samples = 20 value = [19, 1] class = No 1236->1238 1239 entropy = 0.0 samples = 19 value = [19, 0] class = No 1238->1239 1240 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1238->1240 1242 AHEIGHT <= 73.5 entropy = 0.35 samples = 76 value = [71, 5] class = No 1241->1242 1255 SPECEQ_2.0 <= 0.5 entropy = 0.825 samples = 691 value = [512, 179] class = No 1241->1255 1243 APLKIND_4.0 <= 0.5 entropy = 0.247 samples = 73 value = [70, 3] class = No 1242->1243 1252 SUPERVIS_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1242->1252 1244 BEDDAYR <= 0.5 entropy = 0.183 samples = 72 value = [70, 2] class = No 1243->1244 1251 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1243->1251 1245 entropy = 0.0 samples = 55 value = [55, 0] class = No 1244->1245 1246 HIT4A_2.0 <= 0.5 entropy = 0.523 samples = 17 value = [15, 2] class = No 1244->1246 1247 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1246->1247 1248 ALCSTAT_7 <= 0.5 entropy = 0.337 samples = 16 value = [15, 1] class = No 1246->1248 1249 entropy = 0.0 samples = 14 value = [14, 0] class = No 1248->1249 1250 entropy = 1.0 samples = 2 value = [1, 1] class = No 1248->1250 1253 entropy = 0.0 samples = 1 value = [1, 0] class = No 1252->1253 1254 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1252->1254 1256 AHAYFYR_2.0 <= 0.5 entropy = 0.998 samples = 53 value = [28, 25] class = No 1255->1256 1279 DBHVCLN_2.0 <= 0.5 entropy = 0.797 samples = 638 value = [484, 154] class = No 1255->1279 1257 HYBPLEV_4.0 <= 0.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 1256->1257 1260 CLCKTP <= 3.5 entropy = 0.971 samples = 45 value = [27, 18] class = No 1256->1260 1258 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1257->1258 1259 entropy = 0.0 samples = 1 value = [1, 0] class = No 1257->1259 1261 AHCNOYR2 <= 4.5 entropy = 0.999 samples = 31 value = [15, 16] class = Yes 1260->1261 1276 ASICNHC_2.0 <= 0.5 entropy = 0.592 samples = 14 value = [12, 2] class = No 1260->1276 1262 REGION_2 <= 0.5 entropy = 0.959 samples = 21 value = [13, 8] class = No 1261->1262 1273 ASIMEDC_2.0 <= 0.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 1261->1273 1263 CANEV_2.0 <= 0.5 entropy = 0.998 samples = 17 value = [9, 8] class = No 1262->1263 1272 entropy = 0.0 samples = 4 value = [4, 0] class = No 1262->1272 1264 entropy = 0.0 samples = 4 value = [4, 0] class = No 1263->1264 1265 BMI <= 2824.5 entropy = 0.961 samples = 13 value = [5, 8] class = Yes 1263->1265 1266 ADNLONG2_5.0 <= 0.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 1265->1266 1269 ALCSTAT_5 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1265->1269 1267 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1266->1267 1268 entropy = 0.0 samples = 1 value = [1, 0] class = No 1266->1268 1270 entropy = 0.0 samples = 4 value = [4, 0] class = No 1269->1270 1271 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1269->1271 1274 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 1273->1274 1275 entropy = 0.0 samples = 2 value = [2, 0] class = No 1273->1275 1277 entropy = 0.0 samples = 12 value = [12, 0] class = No 1276->1277 1278 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1276->1278 1280 BMI <= 2525.5 entropy = 0.722 samples = 390 value = [312, 78] class = No 1279->1280 1393 LIVYR_2.0 <= 0.5 entropy = 0.889 samples = 248 value = [172, 76] class = No 1279->1393 1281 ASICNHC_3.0 <= 0.5 entropy = 0.458 samples = 145 value = [131, 14] class = No 1280->1281 1312 BMI <= 2540.5 entropy = 0.829 samples = 245 value = [181, 64] class = No 1280->1312 1282 WRKCATA_4.0 <= 0.5 entropy = 0.544 samples = 112 value = [98, 14] class = No 1281->1282 1311 entropy = 0.0 samples = 33 value = [33, 0] class = No 1281->1311 1283 ASISTLV_4.0 <= 0.5 entropy = 0.451 samples = 106 value = [96, 10] class = No 1282->1283 1308 ASISTLV_3.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 1282->1308 1284 YRSWRKPA <= 0.5 entropy = 0.598 samples = 62 value = [53, 9] class = No 1283->1284 1305 BMI <= 1916.5 entropy = 0.156 samples = 44 value = [43, 1] class = No 1283->1305 1285 entropy = 0.0 samples = 13 value = [13, 0] class = No 1284->1285 1286 YRSWRKPA <= 17.5 entropy = 0.688 samples = 49 value = [40, 9] class = No 1284->1286 1287 MRACRPI2_4 <= 0.5 entropy = 0.79 samples = 38 value = [29, 9] class = No 1286->1287 1304 entropy = 0.0 samples = 11 value = [11, 0] class = No 1286->1304 1288 ASISLEEP <= 7.5 entropy = 0.711 samples = 36 value = [29, 7] class = No 1287->1288 1303 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1287->1303 1289 CHPAIN6M_4.0 <= 0.5 entropy = 0.871 samples = 24 value = [17, 7] class = No 1288->1289 1302 entropy = 0.0 samples = 12 value = [12, 0] class = No 1288->1302 1290 ARTH1_2.0 <= 0.5 entropy = 0.722 samples = 20 value = [16, 4] class = No 1289->1290 1299 YRSWRKPA <= 2.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1289->1299 1291 entropy = 0.0 samples = 9 value = [9, 0] class = No 1290->1291 1292 YRSWRKPA <= 16.0 entropy = 0.946 samples = 11 value = [7, 4] class = No 1290->1292 1293 REGION_3 <= 0.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 1292->1293 1298 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1292->1298 1294 entropy = 0.0 samples = 6 value = [6, 0] class = No 1293->1294 1295 YRSWRKPA <= 13.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1293->1295 1296 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1295->1296 1297 entropy = 0.0 samples = 1 value = [1, 0] class = No 1295->1297 1300 entropy = 0.0 samples = 1 value = [1, 0] class = No 1299->1300 1301 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1299->1301 1306 entropy = 1.0 samples = 2 value = [1, 1] class = No 1305->1306 1307 entropy = 0.0 samples = 42 value = [42, 0] class = No 1305->1307 1309 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1308->1309 1310 entropy = 0.0 samples = 2 value = [2, 0] class = No 1308->1310 1313 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1312->1313 1314 AHEIGHT <= 59.5 entropy = 0.815 samples = 242 value = [181, 61] class = No 1312->1314 1315 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1314->1315 1316 BMI <= 3340.0 entropy = 0.805 samples = 240 value = [181, 59] class = No 1314->1316 1317 CHLEV_2.0 <= 0.5 entropy = 0.75 samples = 196 value = [154, 42] class = No 1316->1317 1376 YRSWRKPA <= 16.5 entropy = 0.962 samples = 44 value = [27, 17] class = No 1316->1376 1318 YRSWRKPA <= 7.5 entropy = 0.923 samples = 74 value = [49, 25] class = No 1317->1318 1347 MRACRPI2_4 <= 0.5 entropy = 0.583 samples = 122 value = [105, 17] class = No 1317->1347 1319 AHEARST1_5.0 <= 0.5 entropy = 0.276 samples = 21 value = [20, 1] class = No 1318->1319 1322 HIT2A_2.0 <= 0.5 entropy = 0.994 samples = 53 value = [29, 24] class = No 1318->1322 1320 entropy = 0.0 samples = 20 value = [20, 0] class = No 1319->1320 1321 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1319->1321 1323 APLKIND_2.0 <= 0.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 1322->1323 1326 ALCSTAT_5 <= 0.5 entropy = 0.956 samples = 45 value = [28, 17] class = No 1322->1326 1324 entropy = 0.0 samples = 1 value = [1, 0] class = No 1323->1324 1325 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1323->1325 1327 CHPAIN6M_4.0 <= 0.5 entropy = 0.988 samples = 39 value = [22, 17] class = No 1326->1327 1346 entropy = 0.0 samples = 6 value = [6, 0] class = No 1326->1346 1328 AHEIGHT <= 73.5 entropy = 0.997 samples = 30 value = [14, 16] class = Yes 1327->1328 1343 R_MARITL_2 <= 0.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 1327->1343 1329 ASISLEEP <= 6.5 entropy = 0.975 samples = 27 value = [11, 16] class = Yes 1328->1329 1342 entropy = 0.0 samples = 3 value = [3, 0] class = No 1328->1342 1330 LOCALL1B <= 4.5 entropy = 0.881 samples = 10 value = [7, 3] class = No 1329->1330 1335 SUPERVIS_2.0 <= 0.5 entropy = 0.787 samples = 17 value = [4, 13] class = Yes 1329->1335 1331 PAINLB_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 1330->1331 1334 entropy = 0.0 samples = 5 value = [5, 0] class = No 1330->1334 1332 entropy = 0.0 samples = 2 value = [2, 0] class = No 1331->1332 1333 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1331->1333 1336 AHEARST1_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 1335->1336 1341 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1335->1341 1337 BEDDAYR <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1336->1337 1340 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1336->1340 1338 entropy = 0.0 samples = 4 value = [4, 0] class = No 1337->1338 1339 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1337->1339 1344 entropy = 0.0 samples = 8 value = [8, 0] class = No 1343->1344 1345 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1343->1345 1348 YRSWRKPA <= 16.5 entropy = 0.525 samples = 118 value = [104, 14] class = No 1347->1348 1373 DIBPRE2_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1347->1373 1349 ASICPUSE_4.0 <= 0.5 entropy = 0.659 samples = 82 value = [68, 14] class = No 1348->1349 1372 entropy = 0.0 samples = 36 value = [36, 0] class = No 1348->1372 1350 entropy = 0.0 samples = 24 value = [24, 0] class = No 1349->1350 1351 BEDDAYR <= 1.5 entropy = 0.797 samples = 58 value = [44, 14] class = No 1349->1351 1352 LOCALL1B <= 8.5 entropy = 0.871 samples = 48 value = [34, 14] class = No 1351->1352 1371 entropy = 0.0 samples = 10 value = [10, 0] class = No 1351->1371 1353 AHSTATYR_2.0 <= 0.5 entropy = 0.782 samples = 43 value = [33, 10] class = No 1352->1353 1368 ASIRETR_3.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1352->1368 1354 PDSICKA_2.0 <= 0.5 entropy = 0.712 samples = 41 value = [33, 8] class = No 1353->1354 1367 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1353->1367 1355 BMI <= 2726.0 entropy = 0.877 samples = 27 value = [19, 8] class = No 1354->1355 1366 entropy = 0.0 samples = 14 value = [14, 0] class = No 1354->1366 1356 entropy = 0.0 samples = 8 value = [8, 0] class = No 1355->1356 1357 BMI <= 3061.0 entropy = 0.982 samples = 19 value = [11, 8] class = No 1355->1357 1358 PAINLB_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [6, 8] class = Yes 1357->1358 1365 entropy = 0.0 samples = 5 value = [5, 0] class = No 1357->1365 1359 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1358->1359 1360 AMDLONGR_1.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 1358->1360 1361 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1360->1361 1362 CANEV_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 1360->1362 1363 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1362->1363 1364 entropy = 0.0 samples = 6 value = [6, 0] class = No 1362->1364 1369 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1368->1369 1370 entropy = 0.0 samples = 1 value = [1, 0] class = No 1368->1370 1374 entropy = 0.0 samples = 1 value = [1, 0] class = No 1373->1374 1375 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1373->1375 1377 PAR_STAT_3 <= 0.5 entropy = 0.995 samples = 37 value = [20, 17] class = No 1376->1377 1392 entropy = 0.0 samples = 7 value = [7, 0] class = No 1376->1392 1378 AHEIGHT <= 65.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 1377->1378 1381 SMKSTAT2_3.0 <= 0.5 entropy = 0.961 samples = 26 value = [10, 16] class = Yes 1377->1381 1379 entropy = 0.0 samples = 10 value = [10, 0] class = No 1378->1379 1380 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1378->1380 1382 AHSTATYR_3.0 <= 0.5 entropy = 0.998 samples = 19 value = [10, 9] class = No 1381->1382 1391 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1381->1391 1383 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1382->1383 1384 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 15 value = [10, 5] class = No 1382->1384 1385 ASIRETR_3.0 <= 0.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 1384->1385 1390 entropy = 0.0 samples = 5 value = [5, 0] class = No 1384->1390 1386 BEDDAYR <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 1385->1386 1389 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1385->1389 1387 entropy = 0.0 samples = 5 value = [5, 0] class = No 1386->1387 1388 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1386->1388 1394 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1393->1394 1395 ADNLONG2_2.0 <= 0.5 entropy = 0.882 samples = 246 value = [172, 74] class = No 1393->1395 1396 ALCSTAT_8 <= 0.5 entropy = 0.847 samples = 212 value = [154, 58] class = No 1395->1396 1463 ASISTLV_2.0 <= 0.5 entropy = 0.998 samples = 34 value = [18, 16] class = No 1395->1463 1397 CLCKTP <= 3.5 entropy = 0.867 samples = 201 value = [143, 58] class = No 1396->1397 1462 entropy = 0.0 samples = 11 value = [11, 0] class = No 1396->1462 1398 DBHVWLN_2.0 <= 0.5 entropy = 0.931 samples = 127 value = [83, 44] class = No 1397->1398 1443 YRSWRKPA <= 21.5 entropy = 0.7 samples = 74 value = [60, 14] class = No 1397->1443 1399 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1398->1399 1400 ECIGEV2_2.0 <= 0.5 entropy = 0.916 samples = 124 value = [83, 41] class = No 1398->1400 1401 HIT3A_2.0 <= 0.5 entropy = 0.391 samples = 13 value = [12, 1] class = No 1400->1401 1404 R_MARITL_2 <= 0.5 entropy = 0.943 samples = 111 value = [71, 40] class = No 1400->1404 1402 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1401->1402 1403 entropy = 0.0 samples = 12 value = [12, 0] class = No 1401->1403 1405 CBRCHYR_2.0 <= 0.5 entropy = 0.9 samples = 98 value = [67, 31] class = No 1404->1405 1438 REGION_4 <= 0.5 entropy = 0.89 samples = 13 value = [4, 9] class = Yes 1404->1438 1406 AHEARST1_5.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 1405->1406 1409 ASICPUSE_3.0 <= 0.5 entropy = 0.859 samples = 92 value = [66, 26] class = No 1405->1409 1407 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1406->1407 1408 entropy = 0.0 samples = 1 value = [1, 0] class = No 1406->1408 1410 AHEIGHT <= 74.5 entropy = 0.897 samples = 83 value = [57, 26] class = No 1409->1410 1437 entropy = 0.0 samples = 9 value = [9, 0] class = No 1409->1437 1411 CHDEV_2.0 <= 0.5 entropy = 0.877 samples = 81 value = [57, 24] class = No 1410->1411 1436 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1410->1436 1412 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1411->1412 1413 ASICPUSE_2.0 <= 0.5 entropy = 0.853 samples = 79 value = [57, 22] class = No 1411->1413 1414 WRKLYR4_2.0 <= 0.5 entropy = 0.781 samples = 69 value = [53, 16] class = No 1413->1414 1431 CANEV_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 1413->1431 1415 AHEIGHT <= 64.5 entropy = 0.911 samples = 49 value = [33, 16] class = No 1414->1415 1430 entropy = 0.0 samples = 20 value = [20, 0] class = No 1414->1430 1416 LOCALL1B <= 1.5 entropy = 0.989 samples = 16 value = [7, 9] class = Yes 1415->1416 1421 YRSWRKPA <= 26.5 entropy = 0.746 samples = 33 value = [26, 7] class = No 1415->1421 1417 entropy = 0.0 samples = 5 value = [5, 0] class = No 1416->1417 1418 ASIRETR_4.0 <= 0.5 entropy = 0.684 samples = 11 value = [2, 9] class = Yes 1416->1418 1419 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 1418->1419 1420 entropy = 0.0 samples = 2 value = [2, 0] class = No 1418->1420 1422 CIGAREV2_2.0 <= 0.5 entropy = 0.48 samples = 29 value = [26, 3] class = No 1421->1422 1429 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1421->1429 1423 HIT1A_2.0 <= 0.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 1422->1423 1428 entropy = 0.0 samples = 18 value = [18, 0] class = No 1422->1428 1424 BMI <= 3257.0 entropy = 0.503 samples = 9 value = [8, 1] class = No 1423->1424 1427 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1423->1427 1425 entropy = 0.0 samples = 8 value = [8, 0] class = No 1424->1425 1426 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1424->1426 1432 BMI <= 3052.0 entropy = 0.722 samples = 5 value = [4, 1] class = No 1431->1432 1435 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1431->1435 1433 entropy = 0.0 samples = 4 value = [4, 0] class = No 1432->1433 1434 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1432->1434 1439 ASIMEDC_3.0 <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 1438->1439 1442 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1438->1442 1440 entropy = 0.0 samples = 4 value = [4, 0] class = No 1439->1440 1441 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1439->1441 1444 AHEIGHT <= 65.5 entropy = 0.791 samples = 59 value = [45, 14] class = No 1443->1444 1461 entropy = 0.0 samples = 15 value = [15, 0] class = No 1443->1461 1445 APLKIND_3.0 <= 0.5 entropy = 0.297 samples = 19 value = [18, 1] class = No 1444->1445 1448 BMI <= 2060.0 entropy = 0.91 samples = 40 value = [27, 13] class = No 1444->1448 1446 entropy = 0.0 samples = 18 value = [18, 0] class = No 1445->1446 1447 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1445->1447 1449 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1448->1449 1450 AHEIGHT <= 66.5 entropy = 0.811 samples = 36 value = [27, 9] class = No 1448->1450 1451 ADNLONG2_1.0 <= 0.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 1450->1451 1456 AHEARST1_3.0 <= 0.5 entropy = 0.503 samples = 27 value = [24, 3] class = No 1450->1456 1452 entropy = 0.0 samples = 2 value = [2, 0] class = No 1451->1452 1453 CANEV_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 1451->1453 1454 entropy = 0.0 samples = 1 value = [1, 0] class = No 1453->1454 1455 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1453->1455 1457 ALCSTAT_2 <= 0.5 entropy = 0.242 samples = 25 value = [24, 1] class = No 1456->1457 1460 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1456->1460 1458 entropy = 0.0 samples = 24 value = [24, 0] class = No 1457->1458 1459 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1457->1459 1464 WRKCATA_4.0 <= 0.5 entropy = 0.94 samples = 28 value = [18, 10] class = No 1463->1464 1475 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1463->1475 1465 AASMEV_2.0 <= 0.5 entropy = 0.811 samples = 24 value = [18, 6] class = No 1464->1465 1474 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1464->1474 1466 PAINLB_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 1465->1466 1471 AHSTATYR_2.0 <= 0.5 entropy = 0.503 samples = 18 value = [16, 2] class = No 1465->1471 1467 ECIGEV2_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1466->1467 1470 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1466->1470 1468 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1467->1468 1469 entropy = 0.0 samples = 2 value = [2, 0] class = No 1467->1469 1472 entropy = 0.0 samples = 16 value = [16, 0] class = No 1471->1472 1473 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1471->1473 1477 FLUVACYR_2.0 <= 0.5 entropy = 0.861 samples = 74 value = [53, 21] class = No 1476->1477 1496 BMI <= 1909.0 entropy = 0.992 samples = 288 value = [129, 159] class = Yes 1476->1496 1478 BMI <= 3585.5 entropy = 0.989 samples = 32 value = [14, 18] class = Yes 1477->1478 1489 AHSTATYR_2.0 <= 0.5 entropy = 0.371 samples = 42 value = [39, 3] class = No 1477->1489 1479 ASIMEDC_2.0 <= 0.5 entropy = 0.918 samples = 27 value = [9, 18] class = Yes 1478->1479 1488 entropy = 0.0 samples = 5 value = [5, 0] class = No 1478->1488 1480 AVISACT_2.0 <= 0.5 entropy = 0.993 samples = 20 value = [9, 11] class = Yes 1479->1480 1487 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1479->1487 1481 entropy = 0.0 samples = 4 value = [4, 0] class = No 1480->1481 1482 ALCSTAT_6 <= 0.5 entropy = 0.896 samples = 16 value = [5, 11] class = Yes 1480->1482 1483 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 1482->1483 1484 ASRGYR_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 1482->1484 1485 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1484->1485 1486 entropy = 0.0 samples = 5 value = [5, 0] class = No 1484->1486 1490 entropy = 0.0 samples = 29 value = [29, 0] class = No 1489->1490 1491 YTQU_YG1_2.0 <= 0.5 entropy = 0.779 samples = 13 value = [10, 3] class = No 1489->1491 1492 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1491->1492 1493 APLKIND_6.0 <= 0.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 1491->1493 1494 entropy = 0.0 samples = 10 value = [10, 0] class = No 1493->1494 1495 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1493->1495 1497 entropy = 0.0 samples = 8 value = [8, 0] class = No 1496->1497 1498 BMI <= 2716.5 entropy = 0.987 samples = 280 value = [121, 159] class = Yes 1496->1498 1499 BMI <= 2700.0 entropy = 1.0 samples = 159 value = [81, 78] class = No 1498->1499 1566 DBHVWLY_2.0 <= 0.5 entropy = 0.916 samples = 121 value = [40, 81] class = Yes 1498->1566 1500 AHEIGHT <= 73.5 entropy = 1.0 samples = 154 value = [76, 78] class = Yes 1499->1500 1565 entropy = 0.0 samples = 5 value = [5, 0] class = No 1499->1565 1501 ASISLEEP <= 8.5 entropy = 0.998 samples = 149 value = [71, 78] class = Yes 1500->1501 1564 entropy = 0.0 samples = 5 value = [5, 0] class = No 1500->1564 1502 VIMGLASS_2.0 <= 0.5 entropy = 1.0 samples = 133 value = [68, 65] class = No 1501->1502 1559 ASISTLV_4.0 <= 0.5 entropy = 0.696 samples = 16 value = [3, 13] class = Yes 1501->1559 1503 YRSWRKPA <= 3.0 entropy = 0.994 samples = 103 value = [47, 56] class = Yes 1502->1503 1548 ASISLEEP <= 7.5 entropy = 0.881 samples = 30 value = [21, 9] class = No 1502->1548 1504 ASIMEDC_2.0 <= 0.5 entropy = 0.904 samples = 25 value = [17, 8] class = No 1503->1504 1515 SINYR_2.0 <= 0.5 entropy = 0.961 samples = 78 value = [30, 48] class = Yes 1503->1515 1505 AHEIGHT <= 62.5 entropy = 0.991 samples = 18 value = [10, 8] class = No 1504->1505 1514 entropy = 0.0 samples = 7 value = [7, 0] class = No 1504->1514 1506 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1505->1506 1507 HYBPLEV_3.0 <= 0.5 entropy = 0.918 samples = 15 value = [10, 5] class = No 1505->1507 1508 entropy = 0.0 samples = 6 value = [6, 0] class = No 1507->1508 1509 WRKLYR4_2.0 <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 1507->1509 1510 AHSTATYR_3.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1509->1510 1513 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1509->1513 1511 entropy = 0.0 samples = 4 value = [4, 0] class = No 1510->1511 1512 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1510->1512 1516 AHEIGHT <= 66.5 entropy = 0.702 samples = 21 value = [4, 17] class = Yes 1515->1516 1523 AVISACT_2.0 <= 0.5 entropy = 0.994 samples = 57 value = [26, 31] class = Yes 1515->1523 1517 entropy = 0.0 samples = 14 value = [0, 14] class = Yes 1516->1517 1518 AHCNOYR2 <= 4.0 entropy = 0.985 samples = 7 value = [4, 3] class = No 1516->1518 1519 entropy = 0.0 samples = 3 value = [3, 0] class = No 1518->1519 1520 ASISLEEP <= 7.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1518->1520 1521 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1520->1521 1522 entropy = 0.0 samples = 1 value = [1, 0] class = No 1520->1522 1524 BEDDAYR <= 47.5 entropy = 0.811 samples = 12 value = [9, 3] class = No 1523->1524 1529 HIT3A_2.0 <= 0.5 entropy = 0.956 samples = 45 value = [17, 28] class = Yes 1523->1529 1525 CLCKTP <= 2.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 1524->1525 1528 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1524->1528 1526 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1525->1526 1527 entropy = 0.0 samples = 9 value = [9, 0] class = No 1525->1527 1530 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1529->1530 1531 AHEIGHT <= 65.5 entropy = 0.992 samples = 38 value = [17, 21] class = Yes 1529->1531 1532 ASIMEDC_3.0 <= 0.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 1531->1532 1539 SMKSTAT2_3.0 <= 0.5 entropy = 0.773 samples = 22 value = [5, 17] class = Yes 1531->1539 1533 CLCKTP <= 3.5 entropy = 0.414 samples = 12 value = [11, 1] class = No 1532->1533 1536 ASISLEEP <= 5.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1532->1536 1534 entropy = 0.0 samples = 11 value = [11, 0] class = No 1533->1534 1535 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1533->1535 1537 entropy = 0.0 samples = 1 value = [1, 0] class = No 1536->1537 1538 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1536->1538 1540 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 1539->1540 1541 ASISTLV_4.0 <= 0.5 entropy = 0.994 samples = 11 value = [5, 6] class = Yes 1539->1541 1542 PAR_STAT_2 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 1541->1542 1545 HYBPLEV_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1541->1545 1543 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1542->1543 1544 entropy = 0.0 samples = 1 value = [1, 0] class = No 1542->1544 1546 entropy = 0.0 samples = 4 value = [4, 0] class = No 1545->1546 1547 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1545->1547 1549 BEDDAYR <= 7.0 entropy = 0.485 samples = 19 value = [17, 2] class = No 1548->1549 1554 REGION_4 <= 0.5 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 1548->1554 1550 YRSWRKPA <= 3.0 entropy = 0.918 samples = 6 value = [4, 2] class = No 1549->1550 1553 entropy = 0.0 samples = 13 value = [13, 0] class = No 1549->1553 1551 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1550->1551 1552 entropy = 0.0 samples = 4 value = [4, 0] class = No 1550->1552 1555 AHCNOYR2 <= 6.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1554->1555 1558 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1554->1558 1556 entropy = 0.0 samples = 4 value = [4, 0] class = No 1555->1556 1557 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1555->1557 1560 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 1559->1560 1561 CHPAIN6M_4.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 1559->1561 1562 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1561->1562 1563 entropy = 0.0 samples = 3 value = [3, 0] class = No 1561->1563 1567 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1566->1567 1568 DOINGLWA_5.0 <= 0.5 entropy = 0.935 samples = 114 value = [40, 74] class = Yes 1566->1568 1569 DBHVCLN_2.0 <= 0.5 entropy = 0.996 samples = 56 value = [26, 30] class = Yes 1568->1569 1596 ASIMEDC_3.0 <= 0.5 entropy = 0.797 samples = 58 value = [14, 44] class = Yes 1568->1596 1570 ULCEV_2.0 <= 0.5 entropy = 0.989 samples = 41 value = [23, 18] class = No 1569->1570 1591 YRSWRKPA <= 6.0 entropy = 0.722 samples = 15 value = [3, 12] class = Yes 1569->1591 1571 entropy = 0.0 samples = 6 value = [6, 0] class = No 1570->1571 1572 AHEARST1_2.0 <= 0.5 entropy = 0.999 samples = 35 value = [17, 18] class = Yes 1570->1572 1573 ASICNHC_3.0 <= 0.5 entropy = 0.9 samples = 19 value = [6, 13] class = Yes 1572->1573 1582 BMI <= 3521.0 entropy = 0.896 samples = 16 value = [11, 5] class = No 1572->1582 1574 ARTH1_2.0 <= 0.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 1573->1574 1581 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1573->1581 1575 WRKLYR4_1.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 1574->1575 1578 DIBPRE2_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 1574->1578 1576 entropy = 0.0 samples = 5 value = [5, 0] class = No 1575->1576 1577 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1575->1577 1579 entropy = 0.0 samples = 1 value = [1, 0] class = No 1578->1579 1580 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1578->1580 1583 ASISTLV_2.0 <= 0.5 entropy = 0.75 samples = 14 value = [11, 3] class = No 1582->1583 1590 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1582->1590 1584 entropy = 0.0 samples = 7 value = [7, 0] class = No 1583->1584 1585 DBHVWLN_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 1583->1585 1586 entropy = 0.0 samples = 3 value = [3, 0] class = No 1585->1586 1587 ASICNHC_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1585->1587 1588 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1587->1588 1589 entropy = 0.0 samples = 1 value = [1, 0] class = No 1587->1589 1592 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 1591->1592 1593 BMI <= 2957.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 1591->1593 1594 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1593->1594 1595 entropy = 0.0 samples = 3 value = [3, 0] class = No 1593->1595 1597 DIBPRE2_2.0 <= 0.5 entropy = 0.887 samples = 46 value = [14, 32] class = Yes 1596->1597 1610 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 1596->1610 1598 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 1597->1598 1599 LOCALL1B <= 8.5 entropy = 0.964 samples = 36 value = [14, 22] class = Yes 1597->1599 1600 BMI <= 3853.5 entropy = 0.918 samples = 33 value = [11, 22] class = Yes 1599->1600 1609 entropy = 0.0 samples = 3 value = [3, 0] class = No 1599->1609 1601 CLCKTP <= 2.5 entropy = 0.837 samples = 30 value = [8, 22] class = Yes 1600->1601 1608 entropy = 0.0 samples = 3 value = [3, 0] class = No 1600->1608 1602 AHEARST1_4.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 1601->1602 1605 STREV_2.0 <= 0.5 entropy = 0.559 samples = 23 value = [3, 20] class = Yes 1601->1605 1603 entropy = 0.0 samples = 5 value = [5, 0] class = No 1602->1603 1604 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1602->1604 1606 entropy = 0.0 samples = 3 value = [3, 0] class = No 1605->1606 1607 entropy = 0.0 samples = 20 value = [0, 20] class = Yes 1605->1607 1612 AHCNOYR2 <= 1.5 entropy = 0.906 samples = 373 value = [253, 120] class = No 1611->1612 1757 AHCNOYR2 <= 0.5 entropy = 0.672 samples = 1248 value = [1028, 220] class = No 1611->1757 1613 BEDDAYR <= 1.5 entropy = 0.627 samples = 70 value = [59, 11] class = No 1612->1613 1632 FLUVACYR_2.0 <= 0.5 entropy = 0.942 samples = 303 value = [194, 109] class = No 1612->1632 1614 REGION_3 <= 0.5 entropy = 0.434 samples = 56 value = [51, 5] class = No 1613->1614 1627 ASICNHC_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [8, 6] class = No 1613->1627 1615 R_MARITL_2 <= 0.5 entropy = 0.169 samples = 40 value = [39, 1] class = No 1614->1615 1620 HOURPDA_2.0 <= 0.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 1614->1620 1616 entropy = 0.0 samples = 37 value = [37, 0] class = No 1615->1616 1617 AHEIGHT <= 62.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1615->1617 1618 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1617->1618 1619 entropy = 0.0 samples = 2 value = [2, 0] class = No 1617->1619 1621 PDSICKA_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 1620->1621 1626 entropy = 0.0 samples = 9 value = [9, 0] class = No 1620->1626 1622 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1621->1622 1623 SMKSTAT2_4.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1621->1623 1624 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1623->1624 1625 entropy = 0.0 samples = 3 value = [3, 0] class = No 1623->1625 1628 ASICNHC_3.0 <= 0.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 1627->1628 1631 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1627->1631 1629 entropy = 0.0 samples = 7 value = [7, 0] class = No 1628->1629 1630 entropy = 1.0 samples = 2 value = [1, 1] class = No 1628->1630 1633 BMI <= 3254.0 entropy = 0.985 samples = 180 value = [103, 77] class = No 1632->1633 1718 YRSWRKPA <= 12.5 entropy = 0.827 samples = 123 value = [91, 32] class = No 1632->1718 1634 ASISLEEP <= 7.5 entropy = 0.954 samples = 144 value = [90, 54] class = No 1633->1634 1701 HIT3A_2.0 <= 0.5 entropy = 0.944 samples = 36 value = [13, 23] class = Yes 1633->1701 1635 AVISION_2.0 <= 0.5 entropy = 0.873 samples = 92 value = [65, 27] class = No 1634->1635 1676 ASICNHC_2.0 <= 0.5 entropy = 0.999 samples = 52 value = [25, 27] class = Yes 1634->1676 1636 COPDEV_2.0 <= 0.5 entropy = 1.0 samples = 20 value = [10, 10] class = No 1635->1636 1645 ASISTLV_3.0 <= 0.5 entropy = 0.789 samples = 72 value = [55, 17] class = No 1635->1645 1637 entropy = 0.0 samples = 4 value = [4, 0] class = No 1636->1637 1638 YRSWRKPA <= 11.5 entropy = 0.954 samples = 16 value = [6, 10] class = Yes 1636->1638 1639 EPILEP1_2.0 <= 0.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 1638->1639 1642 HYPEV_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 1638->1642 1640 entropy = 0.0 samples = 1 value = [1, 0] class = No 1639->1640 1641 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1639->1641 1643 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1642->1643 1644 entropy = 0.0 samples = 5 value = [5, 0] class = No 1642->1644 1646 AASMEV_2.0 <= 0.5 entropy = 0.89 samples = 52 value = [36, 16] class = No 1645->1646 1673 WRKCATA_4.0 <= 0.5 entropy = 0.286 samples = 20 value = [19, 1] class = No 1645->1673 1647 AHCNOYR2 <= 5.5 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 1646->1647 1652 ALC1YR_2.0 <= 0.5 entropy = 0.773 samples = 44 value = [34, 10] class = No 1646->1652 1648 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1647->1648 1649 AMIGR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1647->1649 1650 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1649->1650 1651 entropy = 0.0 samples = 2 value = [2, 0] class = No 1649->1651 1653 PAINLB_2.0 <= 0.5 entropy = 0.863 samples = 35 value = [25, 10] class = No 1652->1653 1672 entropy = 0.0 samples = 9 value = [9, 0] class = No 1652->1672 1654 CHLEV_2.0 <= 0.5 entropy = 0.523 samples = 17 value = [15, 2] class = No 1653->1654 1661 BMI <= 2492.0 entropy = 0.991 samples = 18 value = [10, 8] class = No 1653->1661 1655 CLCKTP <= 3.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 1654->1655 1660 entropy = 0.0 samples = 12 value = [12, 0] class = No 1654->1660 1656 CHPAIN6M_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1655->1656 1659 entropy = 0.0 samples = 2 value = [2, 0] class = No 1655->1659 1657 entropy = 0.0 samples = 1 value = [1, 0] class = No 1656->1657 1658 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1656->1658 1662 WRKCATA_5.0 <= 0.5 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 1661->1662 1667 BMI <= 2704.5 entropy = 0.722 samples = 10 value = [8, 2] class = No 1661->1667 1663 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1662->1663 1664 BMI <= 2297.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 1662->1664 1665 entropy = 0.0 samples = 2 value = [2, 0] class = No 1664->1665 1666 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1664->1666 1668 entropy = 0.0 samples = 6 value = [6, 0] class = No 1667->1668 1669 AHCNOYR2 <= 3.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1667->1669 1670 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1669->1670 1671 entropy = 0.0 samples = 2 value = [2, 0] class = No 1669->1671 1674 entropy = 0.0 samples = 19 value = [19, 0] class = No 1673->1674 1675 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1673->1675 1677 ULCEV_2.0 <= 0.5 entropy = 0.995 samples = 46 value = [25, 21] class = No 1676->1677 1700 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1676->1700 1678 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1677->1678 1679 CHPAIN6M_4.0 <= 0.5 entropy = 0.954 samples = 40 value = [25, 15] class = No 1677->1679 1680 AHEIGHT <= 68.5 entropy = 0.999 samples = 29 value = [15, 14] class = No 1679->1680 1697 SPECEQ_2.0 <= 0.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 1679->1697 1681 DIBPRE2_2.0 <= 0.5 entropy = 0.959 samples = 21 value = [8, 13] class = Yes 1680->1681 1694 STREV_2.0 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 1680->1694 1682 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1681->1682 1683 ADNLONG2_1.0 <= 0.5 entropy = 1.0 samples = 16 value = [8, 8] class = No 1681->1683 1684 entropy = 0.0 samples = 4 value = [4, 0] class = No 1683->1684 1685 WRKLYR4_2.0 <= 0.5 entropy = 0.918 samples = 12 value = [4, 8] class = Yes 1683->1685 1686 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1685->1686 1687 AHEIGHT <= 61.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 1685->1687 1688 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1687->1688 1689 BMI <= 2330.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1687->1689 1690 AHEIGHT <= 62.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1689->1690 1693 entropy = 0.0 samples = 3 value = [3, 0] class = No 1689->1693 1691 entropy = 0.0 samples = 1 value = [1, 0] class = No 1690->1691 1692 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1690->1692 1695 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1694->1695 1696 entropy = 0.0 samples = 7 value = [7, 0] class = No 1694->1696 1698 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1697->1698 1699 entropy = 0.0 samples = 10 value = [10, 0] class = No 1697->1699 1702 entropy = 0.0 samples = 3 value = [3, 0] class = No 1701->1702 1703 PAR_STAT_2 <= 0.5 entropy = 0.885 samples = 33 value = [10, 23] class = Yes 1701->1703 1704 ASICNHC_3.0 <= 0.5 entropy = 0.824 samples = 31 value = [8, 23] class = Yes 1703->1704 1717 entropy = 0.0 samples = 2 value = [2, 0] class = No 1703->1717 1705 YRSWRKPA <= 16.5 entropy = 0.559 samples = 23 value = [3, 20] class = Yes 1704->1705 1712 ASIRETR_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 1704->1712 1706 entropy = 0.0 samples = 15 value = [0, 15] class = Yes 1705->1706 1707 ASISLEEP <= 6.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 1705->1707 1708 AHEIGHT <= 68.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1707->1708 1711 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1707->1711 1709 entropy = 0.0 samples = 3 value = [3, 0] class = No 1708->1709 1710 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1708->1710 1713 R_MARITL_3 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1712->1713 1716 entropy = 0.0 samples = 4 value = [4, 0] class = No 1712->1716 1714 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1713->1714 1715 entropy = 0.0 samples = 1 value = [1, 0] class = No 1713->1715 1719 ACOLD2W_2.0 <= 0.5 entropy = 0.956 samples = 69 value = [43, 26] class = No 1718->1719 1744 DIBEV1_3.0 <= 0.5 entropy = 0.503 samples = 54 value = [48, 6] class = No 1718->1744 1720 entropy = 0.0 samples = 11 value = [11, 0] class = No 1719->1720 1721 ALCSTAT_5 <= 0.5 entropy = 0.992 samples = 58 value = [32, 26] class = No 1719->1721 1722 AHEIGHT <= 62.5 entropy = 0.938 samples = 48 value = [31, 17] class = No 1721->1722 1741 REGION_3 <= 0.5 entropy = 0.469 samples = 10 value = [1, 9] class = Yes 1721->1741 1723 entropy = 0.0 samples = 7 value = [7, 0] class = No 1722->1723 1724 WRKCATA_5.0 <= 0.5 entropy = 0.979 samples = 41 value = [24, 17] class = No 1722->1724 1725 YTQU_YG1_2.0 <= 0.5 entropy = 0.998 samples = 36 value = [19, 17] class = No 1724->1725 1740 entropy = 0.0 samples = 5 value = [5, 0] class = No 1724->1740 1726 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1725->1726 1727 BMI <= 2441.5 entropy = 0.974 samples = 32 value = [19, 13] class = No 1725->1727 1728 entropy = 0.0 samples = 7 value = [7, 0] class = No 1727->1728 1729 SINYR_2.0 <= 0.5 entropy = 0.999 samples = 25 value = [12, 13] class = Yes 1727->1729 1730 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1729->1730 1731 ASISLEEP <= 7.5 entropy = 0.985 samples = 21 value = [12, 9] class = No 1729->1731 1732 ALCSTAT_3 <= 0.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 1731->1732 1737 ASIRETR_2.0 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 1731->1737 1733 entropy = 0.0 samples = 8 value = [8, 0] class = No 1732->1733 1734 ASIMEDC_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1732->1734 1735 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1734->1735 1736 entropy = 0.0 samples = 1 value = [1, 0] class = No 1734->1736 1738 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1737->1738 1739 entropy = 0.0 samples = 3 value = [3, 0] class = No 1737->1739 1742 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 1741->1742 1743 entropy = 0.0 samples = 1 value = [1, 0] class = No 1741->1743 1745 AHSTATYR_3.0 <= 0.5 entropy = 0.323 samples = 51 value = [48, 3] class = No 1744->1745 1756 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1744->1756 1746 BMI <= 2446.5 entropy = 0.779 samples = 13 value = [10, 3] class = No 1745->1746 1755 entropy = 0.0 samples = 38 value = [38, 0] class = No 1745->1755 1747 entropy = 0.0 samples = 5 value = [5, 0] class = No 1746->1747 1748 YTQU_YG1_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 1746->1748 1749 entropy = 0.0 samples = 2 value = [2, 0] class = No 1748->1749 1750 ASIMEDC_3.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 1748->1750 1751 BMI <= 3218.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1750->1751 1754 entropy = 0.0 samples = 2 value = [2, 0] class = No 1750->1754 1752 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1751->1752 1753 entropy = 0.0 samples = 1 value = [1, 0] class = No 1751->1753 1758 BMI <= 2118.0 entropy = 0.193 samples = 101 value = [98, 3] class = No 1757->1758 1769 DIBPRE2_2.0 <= 0.5 entropy = 0.7 samples = 1147 value = [930, 217] class = No 1757->1769 1759 BMI <= 2072.0 entropy = 0.722 samples = 10 value = [8, 2] class = No 1758->1759 1764 BMI <= 3437.5 entropy = 0.087 samples = 91 value = [90, 1] class = No 1758->1764 1760 entropy = 0.0 samples = 7 value = [7, 0] class = No 1759->1760 1761 ADNLONG2_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1759->1761 1762 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1761->1762 1763 entropy = 0.0 samples = 1 value = [1, 0] class = No 1761->1763 1765 entropy = 0.0 samples = 79 value = [79, 0] class = No 1764->1765 1766 BMI <= 3480.5 entropy = 0.414 samples = 12 value = [11, 1] class = No 1764->1766 1767 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1766->1767 1768 entropy = 0.0 samples = 11 value = [11, 0] class = No 1766->1768 1770 REGION_3 <= 0.5 entropy = 0.951 samples = 100 value = [63, 37] class = No 1769->1770 1811 HOURPDA_2.0 <= 0.5 entropy = 0.662 samples = 1047 value = [867, 180] class = No 1769->1811 1771 BMI <= 2759.0 entropy = 0.993 samples = 71 value = [39, 32] class = No 1770->1771 1802 HIT3A_2.0 <= 0.5 entropy = 0.663 samples = 29 value = [24, 5] class = No 1770->1802 1772 BMI <= 2489.5 entropy = 0.91 samples = 40 value = [27, 13] class = No 1771->1772 1791 YRSWRKPA <= 9.0 entropy = 0.963 samples = 31 value = [12, 19] class = Yes 1771->1791 1773 YTQU_YG1_2.0 <= 0.5 entropy = 0.993 samples = 20 value = [9, 11] class = Yes 1772->1773 1784 APLKIND_2.0 <= 0.5 entropy = 0.469 samples = 20 value = [18, 2] class = No 1772->1784 1774 entropy = 0.0 samples = 3 value = [3, 0] class = No 1773->1774 1775 ASISTLV_3.0 <= 0.5 entropy = 0.937 samples = 17 value = [6, 11] class = Yes 1773->1775 1776 EPILEP1_2.0 <= 0.5 entropy = 0.65 samples = 12 value = [2, 10] class = Yes 1775->1776 1781 CHPAIN6M_3.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1775->1781 1777 entropy = 0.0 samples = 1 value = [1, 0] class = No 1776->1777 1778 MIEV_2.0 <= 0.5 entropy = 0.439 samples = 11 value = [1, 10] class = Yes 1776->1778 1779 entropy = 1.0 samples = 2 value = [1, 1] class = No 1778->1779 1780 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 1778->1780 1782 entropy = 0.0 samples = 4 value = [4, 0] class = No 1781->1782 1783 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1781->1783 1785 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1784->1785 1790 entropy = 0.0 samples = 14 value = [14, 0] class = No 1784->1790 1786 HYBPLEV_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1785->1786 1789 entropy = 0.0 samples = 3 value = [3, 0] class = No 1785->1789 1787 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1786->1787 1788 entropy = 0.0 samples = 1 value = [1, 0] class = No 1786->1788 1792 CLCKTP <= 2.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 1791->1792 1797 CLCKTP <= 3.5 entropy = 0.65 samples = 18 value = [3, 15] class = Yes 1791->1797 1793 ULCEV_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 1792->1793 1796 entropy = 0.0 samples = 7 value = [7, 0] class = No 1792->1796 1794 entropy = 0.0 samples = 2 value = [2, 0] class = No 1793->1794 1795 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1793->1795 1798 entropy = 0.0 samples = 13 value = [0, 13] class = Yes 1797->1798 1799 AHSTATYR_3.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 1797->1799 1800 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1799->1800 1801 entropy = 0.0 samples = 3 value = [3, 0] class = No 1799->1801 1803 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1802->1803 1804 AINTIL2W_2.0 <= 0.5 entropy = 0.503 samples = 27 value = [24, 3] class = No 1802->1804 1805 AHEARST1_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1804->1805 1808 CLCKTP <= 1.5 entropy = 0.25 samples = 24 value = [23, 1] class = No 1804->1808 1806 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1805->1806 1807 entropy = 0.0 samples = 1 value = [1, 0] class = No 1805->1807 1809 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1808->1809 1810 entropy = 0.0 samples = 23 value = [23, 0] class = No 1808->1810 1812 VIM_GLEV_2.0 <= 0.5 entropy = 0.576 samples = 621 value = [536, 85] class = No 1811->1812 1949 BMI <= 3437.0 entropy = 0.766 samples = 426 value = [331, 95] class = No 1811->1949 1813 AWORPAY_2.0 <= 0.5 entropy = 0.948 samples = 30 value = [19, 11] class = No 1812->1813 1822 AHEIGHT <= 61.5 entropy = 0.544 samples = 591 value = [517, 74] class = No 1812->1822 1814 CHLEV_2.0 <= 0.5 entropy = 0.998 samples = 21 value = [10, 11] class = Yes 1813->1814 1821 entropy = 0.0 samples = 9 value = [9, 0] class = No 1813->1821 1815 BEDDAYR <= 32.0 entropy = 0.469 samples = 10 value = [1, 9] class = Yes 1814->1815 1818 DIBREL_2.0 <= 0.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 1814->1818 1816 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 1815->1816 1817 entropy = 0.0 samples = 1 value = [1, 0] class = No 1815->1817 1819 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1818->1819 1820 entropy = 0.0 samples = 9 value = [9, 0] class = No 1818->1820 1823 JNTSYMP_2.0 <= 0.5 entropy = 0.24 samples = 76 value = [73, 3] class = No 1822->1823 1830 SEX_2 <= 0.5 entropy = 0.579 samples = 515 value = [444, 71] class = No 1822->1830 1824 entropy = 0.0 samples = 54 value = [54, 0] class = No 1823->1824 1825 CHPAIN6M_3.0 <= 0.5 entropy = 0.575 samples = 22 value = [19, 3] class = No 1823->1825 1826 ALCSTAT_3 <= 0.5 entropy = 0.286 samples = 20 value = [19, 1] class = No 1825->1826 1829 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1825->1829 1827 entropy = 0.0 samples = 19 value = [19, 0] class = No 1826->1827 1828 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1826->1828 1831 BMI <= 1796.0 entropy = 0.429 samples = 228 value = [208, 20] class = No 1830->1831 1874 AWEBUSE_2.0 <= 0.5 entropy = 0.675 samples = 287 value = [236, 51] class = No 1830->1874 1832 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1831->1832 1833 AHEIGHT <= 67.5 entropy = 0.401 samples = 226 value = [208, 18] class = No 1831->1833 1834 SMKSTAT2_3.0 <= 0.5 entropy = 0.672 samples = 51 value = [42, 9] class = No 1833->1834 1849 CHDEV_2.0 <= 0.5 entropy = 0.292 samples = 175 value = [166, 9] class = No 1833->1849 1835 ADNLONG2_1.0 <= 0.5 entropy = 0.857 samples = 32 value = [23, 9] class = No 1834->1835 1848 entropy = 0.0 samples = 19 value = [19, 0] class = No 1834->1848 1836 ASICNHC_4.0 <= 0.5 entropy = 0.634 samples = 25 value = [21, 4] class = No 1835->1836 1845 PAINLB_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 1835->1845 1837 entropy = 0.0 samples = 12 value = [12, 0] class = No 1836->1837 1838 MRACRPI2_2 <= 0.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 1836->1838 1839 REGION_4 <= 0.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 1838->1839 1844 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1838->1844 1840 entropy = 0.0 samples = 8 value = [8, 0] class = No 1839->1840 1841 HIT2A_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1839->1841 1842 entropy = 0.0 samples = 1 value = [1, 0] class = No 1841->1842 1843 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1841->1843 1846 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1845->1846 1847 entropy = 0.0 samples = 2 value = [2, 0] class = No 1845->1847 1850 APLKIND_2.0 <= 0.5 entropy = 0.691 samples = 27 value = [22, 5] class = No 1849->1850 1861 SUPERVIS_2.0 <= 0.5 entropy = 0.179 samples = 148 value = [144, 4] class = No 1849->1861 1851 entropy = 0.0 samples = 10 value = [10, 0] class = No 1850->1851 1852 LOCALL1B <= 3.5 entropy = 0.874 samples = 17 value = [12, 5] class = No 1850->1852 1853 CLCKTP <= 2.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 1852->1853 1858 LOCALL1B <= 8.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 1852->1858 1854 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1853->1854 1855 ASIRETR_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1853->1855 1856 entropy = 0.0 samples = 3 value = [3, 0] class = No 1855->1856 1857 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1855->1857 1859 entropy = 0.0 samples = 9 value = [9, 0] class = No 1858->1859 1860 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1858->1860 1862 SMKSTAT2_3.0 <= 0.5 entropy = 0.426 samples = 46 value = [42, 4] class = No 1861->1862 1873 entropy = 0.0 samples = 102 value = [102, 0] class = No 1861->1873 1863 HYBPLEV_3.0 <= 0.5 entropy = 0.634 samples = 25 value = [21, 4] class = No 1862->1863 1872 entropy = 0.0 samples = 21 value = [21, 0] class = No 1862->1872 1864 entropy = 0.0 samples = 10 value = [10, 0] class = No 1863->1864 1865 BEDDAYR <= 2.0 entropy = 0.837 samples = 15 value = [11, 4] class = No 1863->1865 1866 CLCKTP <= 3.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 1865->1866 1871 entropy = 0.0 samples = 5 value = [5, 0] class = No 1865->1871 1867 HYPEV_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 1866->1867 1870 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1866->1870 1868 entropy = 0.0 samples = 6 value = [6, 0] class = No 1867->1868 1869 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1867->1869 1875 PAR_STAT_3 <= 0.5 entropy = 0.757 samples = 188 value = [147, 41] class = No 1874->1875 1930 R_MARITL_4 <= 0.5 entropy = 0.472 samples = 99 value = [89, 10] class = No 1874->1930 1876 WRKLYR4_1.0 <= 0.5 entropy = 0.503 samples = 72 value = [64, 8] class = No 1875->1876 1891 YRSWRKPA <= 26.5 entropy = 0.861 samples = 116 value = [83, 33] class = No 1875->1891 1877 ALCSTAT_8 <= 0.5 entropy = 0.334 samples = 65 value = [61, 4] class = No 1876->1877 1886 BEDDAYR <= 2.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 1876->1886 1878 EPILEP1_2.0 <= 0.5 entropy = 0.208 samples = 61 value = [59, 2] class = No 1877->1878 1883 CHPAIN6M_3.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1877->1883 1879 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1878->1879 1880 ASISLEEP <= 11.5 entropy = 0.122 samples = 60 value = [59, 1] class = No 1878->1880 1881 entropy = 0.0 samples = 59 value = [59, 0] class = No 1880->1881 1882 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1880->1882 1884 entropy = 0.0 samples = 2 value = [2, 0] class = No 1883->1884 1885 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1883->1885 1887 APLKIND_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1886->1887 1890 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1886->1890 1888 entropy = 0.0 samples = 3 value = [3, 0] class = No 1887->1888 1889 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1887->1889 1892 BMI <= 2419.0 entropy = 0.895 samples = 106 value = [73, 33] class = No 1891->1892 1929 entropy = 0.0 samples = 10 value = [10, 0] class = No 1891->1929 1893 AWORPAY_3.0 <= 0.5 entropy = 0.667 samples = 46 value = [38, 8] class = No 1892->1893 1904 ALCSTAT_5 <= 0.5 entropy = 0.98 samples = 60 value = [35, 25] class = No 1892->1904 1894 entropy = 0.0 samples = 23 value = [23, 0] class = No 1893->1894 1895 AHSTATYR_3.0 <= 0.5 entropy = 0.932 samples = 23 value = [15, 8] class = No 1893->1895 1896 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1895->1896 1897 SMKSTAT2_4.0 <= 0.5 entropy = 0.742 samples = 19 value = [15, 4] class = No 1895->1897 1898 PAINLB_2.0 <= 0.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 1897->1898 1903 entropy = 0.0 samples = 10 value = [10, 0] class = No 1897->1903 1899 entropy = 0.0 samples = 4 value = [4, 0] class = No 1898->1899 1900 ARTH1_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1898->1900 1901 entropy = 0.0 samples = 1 value = [1, 0] class = No 1900->1901 1902 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1900->1902 1905 AHEIGHT <= 64.5 entropy = 1.0 samples = 48 value = [24, 24] class = No 1904->1905 1926 LOCALL1B <= 2.5 entropy = 0.414 samples = 12 value = [11, 1] class = No 1904->1926 1906 ASISTLV_4.0 <= 0.5 entropy = 0.902 samples = 22 value = [15, 7] class = No 1905->1906 1917 CLCKTP <= 3.5 entropy = 0.931 samples = 26 value = [9, 17] class = Yes 1905->1917 1907 LOCALL1B <= 6.0 entropy = 0.672 samples = 17 value = [14, 3] class = No 1906->1907 1914 CHPAIN6M_3.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1906->1914 1908 entropy = 0.0 samples = 11 value = [11, 0] class = No 1907->1908 1909 ARTH1_2.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 1907->1909 1910 ASISLEEP <= 8.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1909->1910 1913 entropy = 0.0 samples = 2 value = [2, 0] class = No 1909->1913 1911 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1910->1911 1912 entropy = 0.0 samples = 1 value = [1, 0] class = No 1910->1912 1915 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1914->1915 1916 entropy = 0.0 samples = 1 value = [1, 0] class = No 1914->1916 1918 ECIGEV2_2.0 <= 0.5 entropy = 0.998 samples = 19 value = [9, 10] class = Yes 1917->1918 1925 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1917->1925 1919 entropy = 0.0 samples = 4 value = [4, 0] class = No 1918->1919 1920 LOCALL1B <= 5.5 entropy = 0.918 samples = 15 value = [5, 10] class = Yes 1918->1920 1921 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1920->1921 1922 REGION_3 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 1920->1922 1923 entropy = 0.0 samples = 5 value = [5, 0] class = No 1922->1923 1924 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1922->1924 1927 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1926->1927 1928 entropy = 0.0 samples = 11 value = [11, 0] class = No 1926->1928 1931 CHLEV_2.0 <= 0.5 entropy = 0.328 samples = 83 value = [78, 5] class = No 1930->1931 1944 REGION_3 <= 0.5 entropy = 0.896 samples = 16 value = [11, 5] class = No 1930->1944 1932 BMI <= 3388.5 entropy = 0.562 samples = 38 value = [33, 5] class = No 1931->1932 1943 entropy = 0.0 samples = 45 value = [45, 0] class = No 1931->1943 1933 SMKSTAT2_3.0 <= 0.5 entropy = 0.414 samples = 36 value = [33, 3] class = No 1932->1933 1942 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1932->1942 1934 entropy = 0.0 samples = 21 value = [21, 0] class = No 1933->1934 1935 ARTH1_2.0 <= 0.5 entropy = 0.722 samples = 15 value = [12, 3] class = No 1933->1935 1936 SINYR_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 1935->1936 1941 entropy = 0.0 samples = 8 value = [8, 0] class = No 1935->1941 1937 entropy = 0.0 samples = 3 value = [3, 0] class = No 1936->1937 1938 BMI <= 2908.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1936->1938 1939 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1938->1939 1940 entropy = 0.0 samples = 1 value = [1, 0] class = No 1938->1940 1945 JNTSYMP_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 1944->1945 1948 entropy = 0.0 samples = 8 value = [8, 0] class = No 1944->1948 1946 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1945->1946 1947 entropy = 0.0 samples = 3 value = [3, 0] class = No 1945->1947 1950 PDSICKA_2.0 <= 0.5 entropy = 0.739 samples = 407 value = [322, 85] class = No 1949->1950 2077 ASISTLV_3.0 <= 0.5 entropy = 0.998 samples = 19 value = [9, 10] class = Yes 1949->2077 1951 BMI <= 2637.5 entropy = 0.821 samples = 246 value = [183, 63] class = No 1950->1951 2036 YRSWRKPA <= 10.5 entropy = 0.575 samples = 161 value = [139, 22] class = No 1950->2036 1952 AHCNOYR2 <= 2.5 entropy = 0.699 samples = 143 value = [116, 27] class = No 1951->1952 1991 BEDDAYR <= 24.5 entropy = 0.934 samples = 103 value = [67, 36] class = No 1951->1991 1953 ASISLEEP <= 6.5 entropy = 0.95 samples = 46 value = [29, 17] class = No 1952->1953 1970 AVISION_2.0 <= 0.5 entropy = 0.479 samples = 97 value = [87, 10] class = No 1952->1970 1954 HIT4A_2.0 <= 0.5 entropy = 0.371 samples = 14 value = [13, 1] class = No 1953->1954 1957 ALCSTAT_5 <= 0.5 entropy = 1.0 samples = 32 value = [16, 16] class = No 1953->1957 1955 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1954->1955 1956 entropy = 0.0 samples = 13 value = [13, 0] class = No 1954->1956 1958 PAINLB_2.0 <= 0.5 entropy = 0.975 samples = 27 value = [16, 11] class = No 1957->1958 1969 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1957->1969 1959 entropy = 0.0 samples = 7 value = [7, 0] class = No 1958->1959 1960 AHEIGHT <= 63.0 entropy = 0.993 samples = 20 value = [9, 11] class = Yes 1958->1960 1961 entropy = 0.0 samples = 4 value = [4, 0] class = No 1960->1961 1962 AHEARST1_4.0 <= 0.5 entropy = 0.896 samples = 16 value = [5, 11] class = Yes 1960->1962 1963 ASICPUSE_3.0 <= 0.5 entropy = 0.75 samples = 14 value = [3, 11] class = Yes 1962->1963 1968 entropy = 0.0 samples = 2 value = [2, 0] class = No 1962->1968 1964 ADNLONG2_2.0 <= 0.5 entropy = 0.414 samples = 12 value = [1, 11] class = Yes 1963->1964 1967 entropy = 0.0 samples = 2 value = [2, 0] class = No 1963->1967 1965 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 1964->1965 1966 entropy = 0.0 samples = 1 value = [1, 0] class = No 1964->1966 1971 BEDDAYR <= 0.5 entropy = 0.934 samples = 20 value = [13, 7] class = No 1970->1971 1980 HYPEV_2.0 <= 0.5 entropy = 0.238 samples = 77 value = [74, 3] class = No 1970->1980 1972 entropy = 0.0 samples = 7 value = [7, 0] class = No 1971->1972 1973 YRSWRKPA <= 15.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 1971->1973 1974 REGION_3 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 1973->1974 1979 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1973->1979 1975 AWORPAY_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1974->1975 1978 entropy = 0.0 samples = 5 value = [5, 0] class = No 1974->1978 1976 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1975->1976 1977 entropy = 0.0 samples = 1 value = [1, 0] class = No 1975->1977 1981 ASICPUSE_3.0 <= 0.5 entropy = 0.449 samples = 32 value = [29, 3] class = No 1980->1981 1990 entropy = 0.0 samples = 45 value = [45, 0] class = No 1980->1990 1982 PAINECK_2.0 <= 0.5 entropy = 0.345 samples = 31 value = [29, 2] class = No 1981->1982 1989 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1981->1989 1983 CHPAIN6M_4.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1982->1983 1988 entropy = 0.0 samples = 25 value = [25, 0] class = No 1982->1988 1984 ARTH1_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1983->1984 1987 entropy = 0.0 samples = 3 value = [3, 0] class = No 1983->1987 1985 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1984->1985 1986 entropy = 0.0 samples = 1 value = [1, 0] class = No 1984->1986 1992 AINTIL2W_2.0 <= 0.5 entropy = 0.896 samples = 96 value = [66, 30] class = No 1991->1992 2033 CLCKTP <= 3.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 1991->2033 1993 BEDDAYR <= 22.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 1992->1993 1996 AHCNOYR2 <= 1.5 entropy = 0.852 samples = 90 value = [65, 25] class = No 1992->1996 1994 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1993->1994 1995 entropy = 0.0 samples = 1 value = [1, 0] class = No 1993->1995 1997 entropy = 0.0 samples = 9 value = [9, 0] class = No 1996->1997 1998 AVISION_2.0 <= 0.5 entropy = 0.892 samples = 81 value = [56, 25] class = No 1996->1998 1999 entropy = 0.0 samples = 7 value = [7, 0] class = No 1998->1999 2000 SUPERVIS_2.0 <= 0.5 entropy = 0.923 samples = 74 value = [49, 25] class = No 1998->2000 2001 CHLEV_2.0 <= 0.5 entropy = 0.993 samples = 42 value = [23, 19] class = No 2000->2001 2022 LOCALL1B <= 8.0 entropy = 0.696 samples = 32 value = [26, 6] class = No 2000->2022 2002 YRSWRKPA <= 10.5 entropy = 0.918 samples = 18 value = [6, 12] class = Yes 2001->2002 2011 ALC1YR_2.0 <= 0.5 entropy = 0.871 samples = 24 value = [17, 7] class = No 2001->2011 2003 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2002->2003 2004 AHCNOYR2 <= 6.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 2002->2004 2005 YRSWRKPA <= 14.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 2004->2005 2010 entropy = 0.0 samples = 3 value = [3, 0] class = No 2004->2010 2006 entropy = 0.0 samples = 2 value = [2, 0] class = No 2005->2006 2007 ASICPUSE_3.0 <= 0.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 2005->2007 2008 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2007->2008 2009 entropy = 0.0 samples = 1 value = [1, 0] class = No 2007->2009 2012 CIGAREV2_2.0 <= 0.5 entropy = 0.989 samples = 16 value = [9, 7] class = No 2011->2012 2021 entropy = 0.0 samples = 8 value = [8, 0] class = No 2011->2021 2013 AHCNOYR2 <= 5.0 entropy = 0.811 samples = 12 value = [9, 3] class = No 2012->2013 2020 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2012->2020 2014 entropy = 0.0 samples = 6 value = [6, 0] class = No 2013->2014 2015 ASISTLV_3.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 2013->2015 2016 HYPEV_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2015->2016 2019 entropy = 0.0 samples = 2 value = [2, 0] class = No 2015->2019 2017 entropy = 0.0 samples = 1 value = [1, 0] class = No 2016->2017 2018 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2016->2018 2023 FLUVACYR_2.0 <= 0.5 entropy = 0.503 samples = 27 value = [24, 3] class = No 2022->2023 2030 ARTH1_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 2022->2030 2024 entropy = 0.0 samples = 15 value = [15, 0] class = No 2023->2024 2025 BMI <= 2704.5 entropy = 0.811 samples = 12 value = [9, 3] class = No 2023->2025 2026 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2025->2026 2027 ADNLONG2_4.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 2025->2027 2028 entropy = 0.0 samples = 9 value = [9, 0] class = No 2027->2028 2029 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2027->2029 2031 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2030->2031 2032 entropy = 0.0 samples = 2 value = [2, 0] class = No 2030->2032 2034 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2033->2034 2035 entropy = 0.0 samples = 1 value = [1, 0] class = No 2033->2035 2037 DIBREL_2.0 <= 0.5 entropy = 0.805 samples = 61 value = [46, 15] class = No 2036->2037 2060 CHPAIN6M_2.0 <= 0.5 entropy = 0.366 samples = 100 value = [93, 7] class = No 2036->2060 2038 CANEV_2.0 <= 0.5 entropy = 0.997 samples = 15 value = [7, 8] class = Yes 2037->2038 2047 AMIGR_2.0 <= 0.5 entropy = 0.615 samples = 46 value = [39, 7] class = No 2037->2047 2039 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2038->2039 2040 CLCKTP <= 5.0 entropy = 0.946 samples = 11 value = [7, 4] class = No 2038->2040 2041 AHEARST1_3.0 <= 0.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 2040->2041 2046 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2040->2046 2042 entropy = 0.0 samples = 5 value = [5, 0] class = No 2041->2042 2043 REGION_3 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2041->2043 2044 entropy = 0.0 samples = 2 value = [2, 0] class = No 2043->2044 2045 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2043->2045 2048 YRSWRKPA <= 3.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 2047->2048 2051 ASISLEEP <= 9.5 entropy = 0.469 samples = 40 value = [36, 4] class = No 2047->2051 2049 entropy = 0.0 samples = 3 value = [3, 0] class = No 2048->2049 2050 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2048->2050 2052 LOCALL1B <= 8.5 entropy = 0.303 samples = 37 value = [35, 2] class = No 2051->2052 2057 ASICNHC_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2051->2057 2053 BMI <= 1916.0 entropy = 0.183 samples = 36 value = [35, 1] class = No 2052->2053 2056 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2052->2056 2054 entropy = 1.0 samples = 2 value = [1, 1] class = No 2053->2054 2055 entropy = 0.0 samples = 34 value = [34, 0] class = No 2053->2055 2058 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2057->2058 2059 entropy = 0.0 samples = 1 value = [1, 0] class = No 2057->2059 2061 LOCALL1B <= 8.5 entropy = 0.503 samples = 63 value = [56, 7] class = No 2060->2061 2076 entropy = 0.0 samples = 37 value = [37, 0] class = No 2060->2076 2062 ASICNHC_4.0 <= 0.5 entropy = 0.459 samples = 62 value = [56, 6] class = No 2061->2062 2075 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2061->2075 2063 entropy = 0.0 samples = 26 value = [26, 0] class = No 2062->2063 2064 SMKSTAT2_4.0 <= 0.5 entropy = 0.65 samples = 36 value = [30, 6] class = No 2062->2064 2065 BMI <= 2758.5 entropy = 0.863 samples = 21 value = [15, 6] class = No 2064->2065 2074 entropy = 0.0 samples = 15 value = [15, 0] class = No 2064->2074 2066 VIM_MDEV_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [8, 6] class = No 2065->2066 2073 entropy = 0.0 samples = 7 value = [7, 0] class = No 2065->2073 2067 entropy = 0.0 samples = 4 value = [4, 0] class = No 2066->2067 2068 APLKIND_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 2066->2068 2069 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2068->2069 2070 CIGAREV2_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 2068->2070 2071 entropy = 0.0 samples = 4 value = [4, 0] class = No 2070->2071 2072 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2070->2072 2078 AASMEV_2.0 <= 0.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 2077->2078 2083 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2077->2083 2079 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2078->2079 2080 ALCSTAT_2 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 2078->2080 2081 entropy = 0.0 samples = 9 value = [9, 0] class = No 2080->2081 2082 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2080->2082 2085 AMDLONGR_1.0 <= 0.5 entropy = 0.663 samples = 3311 value = [2740, 571] class = No 2084->2085 2966 AHCNOYR2 <= 0.5 entropy = 0.409 samples = 2876 value = [2640, 236] class = No 2084->2966 2086 AHCNOYR2 <= 1.5 entropy = 0.45 samples = 967 value = [876, 91] class = No 2085->2086 2259 BMI <= 3193.5 entropy = 0.731 samples = 2344 value = [1864, 480] class = No 2085->2259 2087 BMI <= 3843.5 entropy = 0.347 samples = 692 value = [647, 45] class = No 2086->2087 2188 BMI <= 2507.0 entropy = 0.651 samples = 275 value = [229, 46] class = No 2086->2188 2088 YRSWRKPA <= 5.5 entropy = 0.327 samples = 685 value = [644, 41] class = No 2087->2088 2185 PAR_STAT_3 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2087->2185 2089 LOCALL1B <= 6.5 entropy = 0.221 samples = 396 value = [382, 14] class = No 2088->2089 2128 BEDDAYR <= 0.5 entropy = 0.448 samples = 289 value = [262, 27] class = No 2088->2128 2090 AHEIGHT <= 71.5 entropy = 0.269 samples = 304 value = [290, 14] class = No 2089->2090 2127 entropy = 0.0 samples = 92 value = [92, 0] class = No 2089->2127 2091 BMI <= 2785.0 entropy = 0.314 samples = 247 value = [233, 14] class = No 2090->2091 2126 entropy = 0.0 samples = 57 value = [57, 0] class = No 2090->2126 2092 REGION_3 <= 0.5 entropy = 0.211 samples = 180 value = [174, 6] class = No 2091->2092 2111 WRKLYR4_2.0 <= 0.5 entropy = 0.528 samples = 67 value = [59, 8] class = No 2091->2111 2093 REGION_2 <= 0.5 entropy = 0.283 samples = 122 value = [116, 6] class = No 2092->2093 2110 entropy = 0.0 samples = 58 value = [58, 0] class = No 2092->2110 2094 WRKLYR4_1.0 <= 0.5 entropy = 0.388 samples = 79 value = [73, 6] class = No 2093->2094 2109 entropy = 0.0 samples = 43 value = [43, 0] class = No 2093->2109 2095 LOCALL1B <= 3.5 entropy = 0.3 samples = 75 value = [71, 4] class = No 2094->2095 2106 AHEIGHT <= 67.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2094->2106 2096 entropy = 0.0 samples = 38 value = [38, 0] class = No 2095->2096 2097 YRSWRKPA <= 1.5 entropy = 0.494 samples = 37 value = [33, 4] class = No 2095->2097 2098 entropy = 0.0 samples = 17 value = [17, 0] class = No 2097->2098 2099 BEDDAYR <= 1.5 entropy = 0.722 samples = 20 value = [16, 4] class = No 2097->2099 2100 PAINLB_2.0 <= 0.5 entropy = 0.503 samples = 18 value = [16, 2] class = No 2099->2100 2105 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2099->2105 2101 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2100->2101 2102 WRKCATA_3.0 <= 0.5 entropy = 0.323 samples = 17 value = [16, 1] class = No 2100->2102 2103 entropy = 0.0 samples = 16 value = [16, 0] class = No 2102->2103 2104 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2102->2104 2107 entropy = 0.0 samples = 2 value = [2, 0] class = No 2106->2107 2108 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2106->2108 2112 YRSWRKPA <= 0.5 entropy = 0.409 samples = 61 value = [56, 5] class = No 2111->2112 2123 CIGAREV2_2.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 2111->2123 2113 FLUVACYR_2.0 <= 0.5 entropy = 0.722 samples = 20 value = [16, 4] class = No 2112->2113 2120 AHEARST1_3.0 <= 0.5 entropy = 0.165 samples = 41 value = [40, 1] class = No 2112->2120 2114 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2113->2114 2115 DBHVCLN_2.0 <= 0.5 entropy = 0.503 samples = 18 value = [16, 2] class = No 2113->2115 2116 entropy = 0.0 samples = 14 value = [14, 0] class = No 2115->2116 2117 REGION_4 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2115->2117 2118 entropy = 0.0 samples = 2 value = [2, 0] class = No 2117->2118 2119 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2117->2119 2121 entropy = 0.0 samples = 39 value = [39, 0] class = No 2120->2121 2122 entropy = 1.0 samples = 2 value = [1, 1] class = No 2120->2122 2124 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2123->2124 2125 entropy = 0.0 samples = 3 value = [3, 0] class = No 2123->2125 2129 DIBREL_2.0 <= 0.5 entropy = 0.313 samples = 230 value = [217, 13] class = No 2128->2129 2162 ADNLONG2_3.0 <= 0.5 entropy = 0.791 samples = 59 value = [45, 14] class = No 2128->2162 2130 PAR_STAT_3 <= 0.5 entropy = 0.579 samples = 58 value = [50, 8] class = No 2129->2130 2147 BMI <= 2646.0 entropy = 0.19 samples = 172 value = [167, 5] class = No 2129->2147 2131 entropy = 0.0 samples = 24 value = [24, 0] class = No 2130->2131 2132 VIM_MDEV_2.0 <= 0.5 entropy = 0.787 samples = 34 value = [26, 8] class = No 2130->2132 2133 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2132->2133 2134 ADNLONG2_4.0 <= 0.5 entropy = 0.696 samples = 32 value = [26, 6] class = No 2132->2134 2135 ASISTLV_4.0 <= 0.5 entropy = 0.567 samples = 30 value = [26, 4] class = No 2134->2135 2146 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2134->2146 2136 ALCSTAT_5 <= 0.5 entropy = 0.764 samples = 18 value = [14, 4] class = No 2135->2136 2145 entropy = 0.0 samples = 12 value = [12, 0] class = No 2135->2145 2137 AHEIGHT <= 65.5 entropy = 0.567 samples = 15 value = [13, 2] class = No 2136->2137 2142 ASISTLV_3.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2136->2142 2138 CANEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2137->2138 2141 entropy = 0.0 samples = 12 value = [12, 0] class = No 2137->2141 2139 entropy = 0.0 samples = 1 value = [1, 0] class = No 2138->2139 2140 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2138->2140 2143 entropy = 0.0 samples = 1 value = [1, 0] class = No 2142->2143 2144 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2142->2144 2148 entropy = 0.0 samples = 91 value = [91, 0] class = No 2147->2148 2149 YRSWRKPA <= 29.5 entropy = 0.334 samples = 81 value = [76, 5] class = No 2147->2149 2150 BMI <= 2653.5 entropy = 0.183 samples = 72 value = [70, 2] class = No 2149->2150 2157 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 2149->2157 2151 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2150->2151 2152 WRKLYR4_1.0 <= 0.5 entropy = 0.107 samples = 71 value = [70, 1] class = No 2150->2152 2153 entropy = 0.0 samples = 65 value = [65, 0] class = No 2152->2153 2154 YRSWRKPA <= 8.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2152->2154 2155 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2154->2155 2156 entropy = 0.0 samples = 5 value = [5, 0] class = No 2154->2156 2158 CHPAIN6M_3.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 2157->2158 2161 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2157->2161 2159 entropy = 0.0 samples = 6 value = [6, 0] class = No 2158->2159 2160 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2158->2160 2163 ASISLEEP <= 7.5 entropy = 0.642 samples = 49 value = [41, 8] class = No 2162->2163 2180 HIT1A_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 2162->2180 2164 CHPAIN6M_2.0 <= 0.5 entropy = 0.787 samples = 34 value = [26, 8] class = No 2163->2164 2179 entropy = 0.0 samples = 15 value = [15, 0] class = No 2163->2179 2165 ADNLONG2_1.0 <= 0.5 entropy = 0.996 samples = 13 value = [7, 6] class = No 2164->2165 2172 YRSWRKPA <= 31.5 entropy = 0.454 samples = 21 value = [19, 2] class = No 2164->2172 2166 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2165->2166 2167 AHEIGHT <= 69.0 entropy = 0.881 samples = 10 value = [7, 3] class = No 2165->2167 2168 REGION_2 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2167->2168 2171 entropy = 0.0 samples = 6 value = [6, 0] class = No 2167->2171 2169 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2168->2169 2170 entropy = 0.0 samples = 1 value = [1, 0] class = No 2168->2170 2173 AHEIGHT <= 69.5 entropy = 0.286 samples = 20 value = [19, 1] class = No 2172->2173 2178 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2172->2178 2174 entropy = 0.0 samples = 17 value = [17, 0] class = No 2173->2174 2175 YRSWRKPA <= 7.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 2173->2175 2176 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2175->2176 2177 entropy = 0.0 samples = 2 value = [2, 0] class = No 2175->2177 2181 AHCNOYR2 <= 0.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 2180->2181 2184 entropy = 0.0 samples = 3 value = [3, 0] class = No 2180->2184 2182 entropy = 0.0 samples = 1 value = [1, 0] class = No 2181->2182 2183 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2181->2183 2186 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2185->2186 2187 entropy = 0.0 samples = 3 value = [3, 0] class = No 2185->2187 2189 AINTIL2W_2.0 <= 0.5 entropy = 0.416 samples = 131 value = [120, 11] class = No 2188->2189 2212 MRACRPI2_4 <= 0.5 entropy = 0.8 samples = 144 value = [109, 35] class = No 2188->2212 2190 YRSWRKPA <= 5.0 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 2189->2190 2193 SUPERVIS_2.0 <= 0.5 entropy = 0.341 samples = 126 value = [118, 8] class = No 2189->2193 2191 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2190->2191 2192 entropy = 0.0 samples = 2 value = [2, 0] class = No 2190->2192 2194 ASICNHC_4.0 <= 0.5 entropy = 0.684 samples = 33 value = [27, 6] class = No 2193->2194 2205 BEDDAYR <= 12.0 entropy = 0.15 samples = 93 value = [91, 2] class = No 2193->2205 2195 entropy = 0.0 samples = 11 value = [11, 0] class = No 2194->2195 2196 CHLEV_2.0 <= 0.5 entropy = 0.845 samples = 22 value = [16, 6] class = No 2194->2196 2197 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2196->2197 2198 BEDDAYR <= 0.5 entropy = 0.722 samples = 20 value = [16, 4] class = No 2196->2198 2199 entropy = 0.0 samples = 12 value = [12, 0] class = No 2198->2199 2200 ASISTLV_4.0 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 2198->2200 2201 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2200->2201 2202 PAR_STAT_2 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 2200->2202 2203 entropy = 0.0 samples = 4 value = [4, 0] class = No 2202->2203 2204 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2202->2204 2206 ADNLONG2_3.0 <= 0.5 entropy = 0.087 samples = 92 value = [91, 1] class = No 2205->2206 2211 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2205->2211 2207 entropy = 0.0 samples = 82 value = [82, 0] class = No 2206->2207 2208 HIT4A_2.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 2206->2208 2209 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2208->2209 2210 entropy = 0.0 samples = 9 value = [9, 0] class = No 2208->2210 2213 YRSWRKPA <= 24.0 entropy = 0.745 samples = 137 value = [108, 29] class = No 2212->2213 2256 HIT2A_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 2212->2256 2214 YRSWRKPA <= 0.5 entropy = 0.669 samples = 120 value = [99, 21] class = No 2213->2214 2249 AWORPAY_2.0 <= 0.5 entropy = 0.998 samples = 17 value = [9, 8] class = No 2213->2249 2215 ASISLEEP <= 6.5 entropy = 0.98 samples = 24 value = [14, 10] class = No 2214->2215 2226 YRSWRKPA <= 13.5 entropy = 0.514 samples = 96 value = [85, 11] class = No 2214->2226 2216 BMI <= 3471.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 2215->2216 2219 HIT4A_2.0 <= 0.5 entropy = 0.787 samples = 17 value = [13, 4] class = No 2215->2219 2217 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2216->2217 2218 entropy = 0.0 samples = 1 value = [1, 0] class = No 2216->2218 2220 AASMEV_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 2219->2220 2223 R_MARITL_2 <= 0.5 entropy = 0.414 samples = 12 value = [11, 1] class = No 2219->2223 2221 entropy = 0.0 samples = 2 value = [2, 0] class = No 2220->2221 2222 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2220->2222 2224 entropy = 0.0 samples = 11 value = [11, 0] class = No 2223->2224 2225 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2223->2225 2227 BMI <= 2995.5 entropy = 0.597 samples = 76 value = [65, 11] class = No 2226->2227 2248 entropy = 0.0 samples = 20 value = [20, 0] class = No 2226->2248 2228 HIT4A_2.0 <= 0.5 entropy = 0.738 samples = 48 value = [38, 10] class = No 2227->2228 2245 AMDLONGR_5.0 <= 0.5 entropy = 0.222 samples = 28 value = [27, 1] class = No 2227->2245 2229 entropy = 0.0 samples = 10 value = [10, 0] class = No 2228->2229 2230 ASISTLV_4.0 <= 0.5 entropy = 0.831 samples = 38 value = [28, 10] class = No 2228->2230 2231 AHEIGHT <= 68.5 entropy = 0.966 samples = 23 value = [14, 9] class = No 2230->2231 2242 ASICNHC_3.0 <= 0.5 entropy = 0.353 samples = 15 value = [14, 1] class = No 2230->2242 2232 ASISTLV_3.0 <= 0.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 2231->2232 2237 BMI <= 2533.0 entropy = 0.75 samples = 14 value = [11, 3] class = No 2231->2237 2233 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2232->2233 2234 BMI <= 2772.0 entropy = 0.811 samples = 4 value = [3, 1] class = No 2232->2234 2235 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2234->2235 2236 entropy = 0.0 samples = 3 value = [3, 0] class = No 2234->2236 2238 PAR_STAT_3 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2237->2238 2241 entropy = 0.0 samples = 10 value = [10, 0] class = No 2237->2241 2239 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2238->2239 2240 entropy = 0.0 samples = 1 value = [1, 0] class = No 2238->2240 2243 entropy = 0.0 samples = 14 value = [14, 0] class = No 2242->2243 2244 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2242->2244 2246 entropy = 0.0 samples = 27 value = [27, 0] class = No 2245->2246 2247 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2245->2247 2250 BMI <= 2675.0 entropy = 0.811 samples = 12 value = [9, 3] class = No 2249->2250 2255 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2249->2255 2251 AHCNOYR2 <= 2.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2250->2251 2254 entropy = 0.0 samples = 8 value = [8, 0] class = No 2250->2254 2252 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2251->2252 2253 entropy = 0.0 samples = 1 value = [1, 0] class = No 2251->2253 2257 entropy = 0.0 samples = 1 value = [1, 0] class = No 2256->2257 2258 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2256->2258 2260 YRSWRKPA <= 9.5 entropy = 0.695 samples = 2065 value = [1679, 386] class = No 2259->2260 2857 LOCALL1B <= 1.5 entropy = 0.922 samples = 279 value = [185, 94] class = No 2259->2857 2261 CHLEV_2.0 <= 0.5 entropy = 0.624 samples = 1240 value = [1047, 193] class = No 2260->2261 2596 FLUVACYR_2.0 <= 0.5 entropy = 0.785 samples = 825 value = [632, 193] class = No 2260->2596 2262 HYBPLEV_2.0 <= 0.5 entropy = 0.816 samples = 166 value = [124, 42] class = No 2261->2262 2317 CLCKTP <= 1.5 entropy = 0.586 samples = 1074 value = [923, 151] class = No 2261->2317 2263 CLCKTP <= 2.5 entropy = 0.759 samples = 155 value = [121, 34] class = No 2262->2263 2312 SMKSTAT2_3.0 <= 0.5 entropy = 0.845 samples = 11 value = [3, 8] class = Yes 2262->2312 2264 REGION_3 <= 0.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 2263->2264 2271 YRSWRKPA <= 6.5 entropy = 0.702 samples = 142 value = [115, 27] class = No 2263->2271 2265 AHCNOYR2 <= 2.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 2264->2265 2268 ASISTLV_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2264->2268 2266 entropy = 1.0 samples = 2 value = [1, 1] class = No 2265->2266 2267 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2265->2267 2269 entropy = 0.0 samples = 5 value = [5, 0] class = No 2268->2269 2270 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2268->2270 2272 AHSTATYR_3.0 <= 0.5 entropy = 0.763 samples = 122 value = [95, 27] class = No 2271->2272 2311 entropy = 0.0 samples = 20 value = [20, 0] class = No 2271->2311 2273 AHCNOYR2 <= 3.5 entropy = 0.934 samples = 40 value = [26, 14] class = No 2272->2273 2288 YRSWRKPA <= 3.5 entropy = 0.631 samples = 82 value = [69, 13] class = No 2272->2288 2274 ADNLONG2_1.0 <= 0.5 entropy = 0.797 samples = 29 value = [22, 7] class = No 2273->2274 2285 AHEIGHT <= 69.5 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 2273->2285 2275 ASIMEDC_3.0 <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 2274->2275 2280 AHEIGHT <= 72.5 entropy = 0.469 samples = 20 value = [18, 2] class = No 2274->2280 2276 SEX_2 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 2275->2276 2279 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2275->2279 2277 entropy = 0.0 samples = 4 value = [4, 0] class = No 2276->2277 2278 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2276->2278 2281 HYBPLEV_4.0 <= 0.5 entropy = 0.297 samples = 19 value = [18, 1] class = No 2280->2281 2284 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2280->2284 2282 entropy = 0.0 samples = 18 value = [18, 0] class = No 2281->2282 2283 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2281->2283 2286 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2285->2286 2287 entropy = 0.0 samples = 4 value = [4, 0] class = No 2285->2287 2289 REGION_2 <= 0.5 entropy = 0.761 samples = 59 value = [46, 13] class = No 2288->2289 2310 entropy = 0.0 samples = 23 value = [23, 0] class = No 2288->2310 2290 ASISLEEP <= 6.5 entropy = 0.859 samples = 46 value = [33, 13] class = No 2289->2290 2309 entropy = 0.0 samples = 13 value = [13, 0] class = No 2289->2309 2291 ULCEV_2.0 <= 0.5 entropy = 0.997 samples = 15 value = [7, 8] class = Yes 2290->2291 2298 AHAYFYR_2.0 <= 0.5 entropy = 0.637 samples = 31 value = [26, 5] class = No 2290->2298 2292 entropy = 0.0 samples = 5 value = [5, 0] class = No 2291->2292 2293 ASISTLV_3.0 <= 0.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 2291->2293 2294 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2293->2294 2295 PAR_STAT_3 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2293->2295 2296 entropy = 0.0 samples = 2 value = [2, 0] class = No 2295->2296 2297 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2295->2297 2299 AHEIGHT <= 66.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2298->2299 2302 SUPERVIS_2.0 <= 0.5 entropy = 0.491 samples = 28 value = [25, 3] class = No 2298->2302 2300 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2299->2300 2301 entropy = 0.0 samples = 1 value = [1, 0] class = No 2299->2301 2303 BEDDAYR <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 2302->2303 2308 entropy = 0.0 samples = 19 value = [19, 0] class = No 2302->2308 2304 AVISACT_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2303->2304 2307 entropy = 0.0 samples = 5 value = [5, 0] class = No 2303->2307 2305 entropy = 0.0 samples = 1 value = [1, 0] class = No 2304->2305 2306 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2304->2306 2313 PAR_STAT_3 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 2312->2313 2316 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2312->2316 2314 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2313->2314 2315 entropy = 0.0 samples = 3 value = [3, 0] class = No 2313->2315 2318 AASMEV_2.0 <= 0.5 entropy = 0.315 samples = 123 value = [116, 7] class = No 2317->2318 2335 MRACRPI2_4 <= 0.5 entropy = 0.613 samples = 951 value = [807, 144] class = No 2317->2335 2319 PDSICKA_2.0 <= 0.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 2318->2319 2324 LOCALL1B <= 2.5 entropy = 0.184 samples = 107 value = [104, 3] class = No 2318->2324 2320 entropy = 0.0 samples = 9 value = [9, 0] class = No 2319->2320 2321 DBHVCLN_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2319->2321 2322 entropy = 0.0 samples = 3 value = [3, 0] class = No 2321->2322 2323 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2321->2323 2325 EPILEP1_2.0 <= 0.5 entropy = 0.575 samples = 22 value = [19, 3] class = No 2324->2325 2334 entropy = 0.0 samples = 85 value = [85, 0] class = No 2324->2334 2326 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2325->2326 2327 AHCNOYR2 <= 1.5 entropy = 0.454 samples = 21 value = [19, 2] class = No 2325->2327 2328 CHPAIN6M_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 2327->2328 2333 entropy = 0.0 samples = 16 value = [16, 0] class = No 2327->2333 2329 entropy = 0.0 samples = 2 value = [2, 0] class = No 2328->2329 2330 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2328->2330 2331 entropy = 0.0 samples = 1 value = [1, 0] class = No 2330->2331 2332 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2330->2332 2336 SMKSTAT2_2.0 <= 0.5 entropy = 0.579 samples = 869 value = [749, 120] class = No 2335->2336 2563 BMI <= 2307.0 entropy = 0.872 samples = 82 value = [58, 24] class = No 2335->2563 2337 ALC1YR_2.0 <= 0.5 entropy = 0.593 samples = 836 value = [716, 120] class = No 2336->2337 2562 entropy = 0.0 samples = 33 value = [33, 0] class = No 2336->2562 2338 AHCNOYR2 <= 5.5 entropy = 0.541 samples = 660 value = [578, 82] class = No 2337->2338 2503 ASIMEDC_2.0 <= 0.5 entropy = 0.753 samples = 176 value = [138, 38] class = No 2337->2503 2339 DBHVWLY_2.0 <= 0.5 entropy = 0.499 samples = 584 value = [520, 64] class = No 2338->2339 2476 BMI <= 2672.5 entropy = 0.79 samples = 76 value = [58, 18] class = No 2338->2476 2340 WRKLYR4_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2339->2340 2343 SPECEQ_2.0 <= 0.5 entropy = 0.485 samples = 580 value = [519, 61] class = No 2339->2343 2341 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2340->2341 2342 entropy = 0.0 samples = 1 value = [1, 0] class = No 2340->2342 2344 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2343->2344 2345 ASICPUSE_3.0 <= 0.5 entropy = 0.476 samples = 578 value = [519, 59] class = No 2343->2345 2346 CLCKTP <= 3.5 entropy = 0.492 samples = 549 value = [490, 59] class = No 2345->2346 2475 entropy = 0.0 samples = 29 value = [29, 0] class = No 2345->2475 2347 PAINECK_2.0 <= 0.5 entropy = 0.568 samples = 329 value = [285, 44] class = No 2346->2347 2440 AHEIGHT <= 68.5 entropy = 0.359 samples = 220 value = [205, 15] class = No 2346->2440 2348 BMI <= 2404.0 entropy = 0.961 samples = 26 value = [16, 10] class = No 2347->2348 2361 HIT3A_2.0 <= 0.5 entropy = 0.507 samples = 303 value = [269, 34] class = No 2347->2361 2349 HYBPLEV_5.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 2348->2349 2352 ADNLONG2_2.0 <= 0.5 entropy = 0.989 samples = 16 value = [7, 9] class = Yes 2348->2352 2350 entropy = 0.0 samples = 9 value = [9, 0] class = No 2349->2350 2351 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2349->2351 2353 LOCALL1B <= 2.5 entropy = 0.89 samples = 13 value = [4, 9] class = Yes 2352->2353 2360 entropy = 0.0 samples = 3 value = [3, 0] class = No 2352->2360 2354 entropy = 0.0 samples = 2 value = [2, 0] class = No 2353->2354 2355 YTQU_YG1_2.0 <= 0.5 entropy = 0.684 samples = 11 value = [2, 9] class = Yes 2353->2355 2356 FLUVACYR_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2355->2356 2359 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2355->2359 2357 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2356->2357 2358 entropy = 0.0 samples = 2 value = [2, 0] class = No 2356->2358 2362 HIT4A_2.0 <= 0.5 entropy = 0.733 samples = 73 value = [58, 15] class = No 2361->2362 2389 APLKIND_2.0 <= 0.5 entropy = 0.411 samples = 230 value = [211, 19] class = No 2361->2389 2363 ASISLEEP <= 7.5 entropy = 0.544 samples = 40 value = [35, 5] class = No 2362->2363 2374 DBHVWLN_2.0 <= 0.5 entropy = 0.885 samples = 33 value = [23, 10] class = No 2362->2374 2364 LOCALL1B <= 7.5 entropy = 0.722 samples = 25 value = [20, 5] class = No 2363->2364 2373 entropy = 0.0 samples = 15 value = [15, 0] class = No 2363->2373 2365 AHEIGHT <= 62.5 entropy = 0.896 samples = 16 value = [11, 5] class = No 2364->2365 2372 entropy = 0.0 samples = 9 value = [9, 0] class = No 2364->2372 2366 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2365->2366 2367 AVISACT_2.0 <= 0.5 entropy = 0.75 samples = 14 value = [11, 3] class = No 2365->2367 2368 BMI <= 2322.0 entropy = 1.0 samples = 6 value = [3, 3] class = No 2367->2368 2371 entropy = 0.0 samples = 8 value = [8, 0] class = No 2367->2371 2369 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2368->2369 2370 entropy = 0.0 samples = 3 value = [3, 0] class = No 2368->2370 2375 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2374->2375 2376 LOCALL1B <= 5.5 entropy = 0.824 samples = 31 value = [23, 8] class = No 2374->2376 2377 AVISION_2.0 <= 0.5 entropy = 0.353 samples = 15 value = [14, 1] class = No 2376->2377 2380 ASISLEEP <= 6.5 entropy = 0.989 samples = 16 value = [9, 7] class = No 2376->2380 2378 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2377->2378 2379 entropy = 0.0 samples = 14 value = [14, 0] class = No 2377->2379 2381 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2380->2381 2382 ARTH1_2.0 <= 0.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 2380->2382 2383 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2382->2383 2384 AINTIL2W_2.0 <= 0.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 2382->2384 2385 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2384->2385 2386 AHEARST1_2.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 2384->2386 2387 entropy = 0.0 samples = 8 value = [8, 0] class = No 2386->2387 2388 entropy = 1.0 samples = 2 value = [1, 1] class = No 2386->2388 2390 WRKCATA_4.0 <= 0.5 entropy = 0.137 samples = 52 value = [51, 1] class = No 2389->2390 2393 CHPAIN6M_2.0 <= 0.5 entropy = 0.473 samples = 178 value = [160, 18] class = No 2389->2393 2391 entropy = 0.0 samples = 51 value = [51, 0] class = No 2390->2391 2392 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2390->2392 2394 LOCALL1B <= 5.5 entropy = 0.318 samples = 104 value = [98, 6] class = No 2393->2394 2413 HOURPDA_2.0 <= 0.5 entropy = 0.639 samples = 74 value = [62, 12] class = No 2393->2413 2395 R_MARITL_4 <= 0.5 entropy = 0.464 samples = 61 value = [55, 6] class = No 2394->2395 2412 entropy = 0.0 samples = 43 value = [43, 0] class = No 2394->2412 2396 AHEARST1_2.0 <= 0.5 entropy = 0.639 samples = 37 value = [31, 6] class = No 2395->2396 2411 entropy = 0.0 samples = 24 value = [24, 0] class = No 2395->2411 2397 DBHVWLN_2.0 <= 0.5 entropy = 0.391 samples = 26 value = [24, 2] class = No 2396->2397 2404 AHCNOYR2 <= 1.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 2396->2404 2398 HIT1A_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 2397->2398 2403 entropy = 0.0 samples = 20 value = [20, 0] class = No 2397->2403 2399 ASISTLV_3.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2398->2399 2402 entropy = 0.0 samples = 3 value = [3, 0] class = No 2398->2402 2400 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2399->2400 2401 entropy = 0.0 samples = 1 value = [1, 0] class = No 2399->2401 2405 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2404->2405 2406 VIMGLASS_2.0 <= 0.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 2404->2406 2407 entropy = 0.0 samples = 6 value = [6, 0] class = No 2406->2407 2408 AWORPAY_3.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2406->2408 2409 entropy = 0.0 samples = 1 value = [1, 0] class = No 2408->2409 2410 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2408->2410 2414 ADNLONG2_3.0 <= 0.5 entropy = 0.391 samples = 39 value = [36, 3] class = No 2413->2414 2423 AVISACT_2.0 <= 0.5 entropy = 0.822 samples = 35 value = [26, 9] class = No 2413->2423 2415 DOINGLWA_5.0 <= 0.5 entropy = 0.183 samples = 36 value = [35, 1] class = No 2414->2415 2420 YRSWRKPA <= 1.0 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2414->2420 2416 entropy = 0.0 samples = 33 value = [33, 0] class = No 2415->2416 2417 AHEIGHT <= 65.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 2415->2417 2418 entropy = 0.0 samples = 2 value = [2, 0] class = No 2417->2418 2419 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2417->2419 2421 entropy = 0.0 samples = 1 value = [1, 0] class = No 2420->2421 2422 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2420->2422 2424 AHSTATYR_3.0 <= 0.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 2423->2424 2431 SUPERVIS_2.0 <= 0.5 entropy = 0.634 samples = 25 value = [21, 4] class = No 2423->2431 2425 entropy = 0.0 samples = 3 value = [3, 0] class = No 2424->2425 2426 ALCSTAT_7 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 2424->2426 2427 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2426->2427 2428 BEDDAYR <= 2.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2426->2428 2429 entropy = 0.0 samples = 2 value = [2, 0] class = No 2428->2429 2430 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2428->2430 2432 entropy = 0.0 samples = 11 value = [11, 0] class = No 2431->2432 2433 AMIGR_2.0 <= 0.5 entropy = 0.863 samples = 14 value = [10, 4] class = No 2431->2433 2434 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2433->2434 2435 R_MARITL_2 <= 0.5 entropy = 0.65 samples = 12 value = [10, 2] class = No 2433->2435 2436 PAINLB_2.0 <= 0.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 2435->2436 2439 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2435->2439 2437 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2436->2437 2438 entropy = 0.0 samples = 10 value = [10, 0] class = No 2436->2438 2441 DBHVCLN_2.0 <= 0.5 entropy = 0.443 samples = 152 value = [138, 14] class = No 2440->2441 2472 BMI <= 3099.5 entropy = 0.111 samples = 68 value = [67, 1] class = No 2440->2472 2442 CHPAIN6M_2.0 <= 0.5 entropy = 0.284 samples = 101 value = [96, 5] class = No 2441->2442 2455 BEDDAYR <= 3.5 entropy = 0.672 samples = 51 value = [42, 9] class = No 2441->2455 2443 FLUVACYR_2.0 <= 0.5 entropy = 0.424 samples = 58 value = [53, 5] class = No 2442->2443 2454 entropy = 0.0 samples = 43 value = [43, 0] class = No 2442->2454 2444 entropy = 0.0 samples = 27 value = [27, 0] class = No 2443->2444 2445 ACOLD2W_2.0 <= 0.5 entropy = 0.637 samples = 31 value = [26, 5] class = No 2443->2445 2446 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2445->2446 2447 LOCALL1B <= 1.5 entropy = 0.48 samples = 29 value = [26, 3] class = No 2445->2447 2448 SMKSTAT2_4.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2447->2448 2451 ALCSTAT_5 <= 0.5 entropy = 0.242 samples = 25 value = [24, 1] class = No 2447->2451 2449 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2448->2449 2450 entropy = 0.0 samples = 2 value = [2, 0] class = No 2448->2450 2452 entropy = 0.0 samples = 24 value = [24, 0] class = No 2451->2452 2453 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2451->2453 2456 VIMGLASS_2.0 <= 0.5 entropy = 0.592 samples = 49 value = [42, 7] class = No 2455->2456 2471 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2455->2471 2457 PAINFACE_2.0 <= 0.5 entropy = 0.216 samples = 29 value = [28, 1] class = No 2456->2457 2462 LOCALL1B <= 5.5 entropy = 0.881 samples = 20 value = [14, 6] class = No 2456->2462 2458 REGION_2 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 2457->2458 2461 entropy = 0.0 samples = 25 value = [25, 0] class = No 2457->2461 2459 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2458->2459 2460 entropy = 0.0 samples = 3 value = [3, 0] class = No 2458->2460 2463 SINYR_2.0 <= 0.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 2462->2463 2466 SUPERVIS_2.0 <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 2462->2466 2464 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2463->2464 2465 entropy = 0.0 samples = 10 value = [10, 0] class = No 2463->2465 2467 entropy = 0.0 samples = 3 value = [3, 0] class = No 2466->2467 2468 LOCALL1B <= 8.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 2466->2468 2469 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2468->2469 2470 entropy = 0.0 samples = 1 value = [1, 0] class = No 2468->2470 2473 entropy = 0.0 samples = 67 value = [67, 0] class = No 2472->2473 2474 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2472->2474 2477 AHEIGHT <= 60.5 entropy = 0.636 samples = 56 value = [47, 9] class = No 2476->2477 2494 DBHVCLN_2.0 <= 0.5 entropy = 0.993 samples = 20 value = [11, 9] class = No 2476->2494 2478 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2477->2478 2479 SEX_2 <= 0.5 entropy = 0.556 samples = 54 value = [47, 7] class = No 2477->2479 2480 DBHVCLN_2.0 <= 0.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 2479->2480 2485 REGION_3 <= 0.5 entropy = 0.365 samples = 43 value = [40, 3] class = No 2479->2485 2481 entropy = 0.0 samples = 6 value = [6, 0] class = No 2480->2481 2482 PAINLB_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2480->2482 2483 entropy = 0.0 samples = 1 value = [1, 0] class = No 2482->2483 2484 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2482->2484 2486 entropy = 0.0 samples = 32 value = [32, 0] class = No 2485->2486 2487 AWORPAY_3.0 <= 0.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 2485->2487 2488 entropy = 0.0 samples = 5 value = [5, 0] class = No 2487->2488 2489 R_MARITL_4 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 2487->2489 2490 ALCSTAT_3 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 2489->2490 2493 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2489->2493 2491 entropy = 0.0 samples = 3 value = [3, 0] class = No 2490->2491 2492 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2490->2492 2495 ASIRETR_2.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 2494->2495 2498 ASIMEDC_3.0 <= 0.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 2494->2498 2496 entropy = 0.0 samples = 9 value = [9, 0] class = No 2495->2496 2497 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2495->2497 2499 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2498->2499 2500 CLCKTP <= 2.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2498->2500 2501 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2500->2501 2502 entropy = 0.0 samples = 2 value = [2, 0] class = No 2500->2502 2504 VIMGLASS_2.0 <= 0.5 entropy = 0.642 samples = 141 value = [118, 23] class = No 2503->2504 2547 REGION_3 <= 0.5 entropy = 0.985 samples = 35 value = [20, 15] class = No 2503->2547 2505 BMI <= 1953.5 entropy = 0.767 samples = 85 value = [66, 19] class = No 2504->2505 2538 YRSWRKPA <= 3.5 entropy = 0.371 samples = 56 value = [52, 4] class = No 2504->2538 2506 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2505->2506 2507 BMI <= 2944.0 entropy = 0.731 samples = 83 value = [66, 17] class = No 2505->2507 2508 LOCALL1B <= 7.5 entropy = 0.645 samples = 73 value = [61, 12] class = No 2507->2508 2533 DBHVWLN_2.0 <= 0.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 2507->2533 2509 YRSWRKPA <= 3.5 entropy = 0.715 samples = 61 value = [49, 12] class = No 2508->2509 2532 entropy = 0.0 samples = 12 value = [12, 0] class = No 2508->2532 2510 SINYR_2.0 <= 0.5 entropy = 0.82 samples = 43 value = [32, 11] class = No 2509->2510 2529 R_MARITL_2 <= 0.5 entropy = 0.31 samples = 18 value = [17, 1] class = No 2509->2529 2511 entropy = 0.0 samples = 6 value = [6, 0] class = No 2510->2511 2512 AHEIGHT <= 71.5 entropy = 0.878 samples = 37 value = [26, 11] class = No 2510->2512 2513 ECIGEV2_2.0 <= 0.5 entropy = 0.822 samples = 35 value = [26, 9] class = No 2512->2513 2528 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2512->2528 2514 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2513->2514 2515 CHPAIN6M_4.0 <= 0.5 entropy = 0.746 samples = 33 value = [26, 7] class = No 2513->2515 2516 ASIMEDC_3.0 <= 0.5 entropy = 0.637 samples = 31 value = [26, 5] class = No 2515->2516 2527 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2515->2527 2517 AHCNOYR2 <= 1.5 entropy = 0.286 samples = 20 value = [19, 1] class = No 2516->2517 2520 BMI <= 2797.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 2516->2520 2518 entropy = 1.0 samples = 2 value = [1, 1] class = No 2517->2518 2519 entropy = 0.0 samples = 18 value = [18, 0] class = No 2517->2519 2521 REGION_2 <= 0.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 2520->2521 2526 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2520->2526 2522 entropy = 0.0 samples = 5 value = [5, 0] class = No 2521->2522 2523 APLKIND_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2521->2523 2524 entropy = 0.0 samples = 2 value = [2, 0] class = No 2523->2524 2525 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2523->2525 2530 entropy = 0.0 samples = 17 value = [17, 0] class = No 2529->2530 2531 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2529->2531 2534 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2533->2534 2535 BEDDAYR <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 2533->2535 2536 entropy = 0.0 samples = 5 value = [5, 0] class = No 2535->2536 2537 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2535->2537 2539 entropy = 0.0 samples = 43 value = [43, 0] class = No 2538->2539 2540 LOCALL1B <= 3.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 2538->2540 2541 entropy = 0.0 samples = 6 value = [6, 0] class = No 2540->2541 2542 AWORPAY_3.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2540->2542 2543 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2542->2543 2544 ECIGEV2_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 2542->2544 2545 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2544->2545 2546 entropy = 0.0 samples = 3 value = [3, 0] class = No 2544->2546 2548 DOINGLWA_5.0 <= 0.5 entropy = 0.792 samples = 21 value = [16, 5] class = No 2547->2548 2555 HOURPDA_2.0 <= 0.5 entropy = 0.863 samples = 14 value = [4, 10] class = Yes 2547->2555 2549 entropy = 0.0 samples = 14 value = [14, 0] class = No 2548->2549 2550 ASICNHC_3.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 2548->2550 2551 BMI <= 2405.0 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 2550->2551 2554 entropy = 0.0 samples = 1 value = [1, 0] class = No 2550->2554 2552 entropy = 0.0 samples = 1 value = [1, 0] class = No 2551->2552 2553 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2551->2553 2556 AHCNOYR2 <= 1.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 2555->2556 2561 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2555->2561 2557 entropy = 0.0 samples = 3 value = [3, 0] class = No 2556->2557 2558 SMKSTAT2_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2556->2558 2559 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2558->2559 2560 entropy = 0.0 samples = 1 value = [1, 0] class = No 2558->2560 2564 ASIRETR_3.0 <= 0.5 entropy = 0.995 samples = 35 value = [19, 16] class = No 2563->2564 2583 ALC1YR_2.0 <= 0.5 entropy = 0.658 samples = 47 value = [39, 8] class = No 2563->2583 2565 SEX_2 <= 0.5 entropy = 0.931 samples = 26 value = [17, 9] class = No 2564->2565 2578 DIBREL_2.0 <= 0.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 2564->2578 2566 ALCSTAT_7 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2565->2566 2569 FLUVACYR_2.0 <= 0.5 entropy = 0.792 samples = 21 value = [16, 5] class = No 2565->2569 2567 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2566->2567 2568 entropy = 0.0 samples = 1 value = [1, 0] class = No 2566->2568 2570 entropy = 0.0 samples = 8 value = [8, 0] class = No 2569->2570 2571 ADNLONG2_1.0 <= 0.5 entropy = 0.961 samples = 13 value = [8, 5] class = No 2569->2571 2572 entropy = 0.0 samples = 5 value = [5, 0] class = No 2571->2572 2573 AMIGR_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 2571->2573 2574 entropy = 0.0 samples = 2 value = [2, 0] class = No 2573->2574 2575 WRKCATA_3.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 2573->2575 2576 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2575->2576 2577 entropy = 0.0 samples = 1 value = [1, 0] class = No 2575->2577 2579 ALCSTAT_6 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2578->2579 2582 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2578->2582 2580 entropy = 0.0 samples = 2 value = [2, 0] class = No 2579->2580 2581 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2579->2581 2584 BMI <= 2464.5 entropy = 0.887 samples = 23 value = [16, 7] class = No 2583->2584 2593 AWEBUSE_2.0 <= 0.5 entropy = 0.25 samples = 24 value = [23, 1] class = No 2583->2593 2585 entropy = 0.0 samples = 9 value = [9, 0] class = No 2584->2585 2586 ASICNHC_3.0 <= 0.5 entropy = 1.0 samples = 14 value = [7, 7] class = No 2584->2586 2587 BEDDAYR <= 0.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 2586->2587 2592 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2586->2592 2588 entropy = 0.0 samples = 6 value = [6, 0] class = No 2587->2588 2589 ASIMEDC_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2587->2589 2590 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2589->2590 2591 entropy = 0.0 samples = 1 value = [1, 0] class = No 2589->2591 2594 entropy = 0.0 samples = 23 value = [23, 0] class = No 2593->2594 2595 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2593->2595 2597 ASIMEDC_3.0 <= 0.5 entropy = 0.85 samples = 442 value = [320, 122] class = No 2596->2597 2746 BEDDAYR <= 3.5 entropy = 0.692 samples = 383 value = [312, 71] class = No 2596->2746 2598 BMI <= 3013.5 entropy = 0.794 samples = 305 value = [232, 73] class = No 2597->2598 2699 CHLEV_2.0 <= 0.5 entropy = 0.941 samples = 137 value = [88, 49] class = No 2597->2699 2599 SMKSTAT2_2.0 <= 0.5 entropy = 0.756 samples = 285 value = [223, 62] class = No 2598->2599 2692 BMI <= 3062.5 entropy = 0.993 samples = 20 value = [9, 11] class = Yes 2598->2692 2600 YTQU_YG1_2.0 <= 0.5 entropy = 0.74 samples = 282 value = [223, 59] class = No 2599->2600 2691 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2599->2691 2601 PAINECK_2.0 <= 0.5 entropy = 0.391 samples = 52 value = [48, 4] class = No 2600->2601 2608 ASIRETR_2.0 <= 0.5 entropy = 0.794 samples = 230 value = [175, 55] class = No 2600->2608 2602 HIT4A_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 2601->2602 2605 AHEARST1_3.0 <= 0.5 entropy = 0.156 samples = 44 value = [43, 1] class = No 2601->2605 2603 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2602->2603 2604 entropy = 0.0 samples = 5 value = [5, 0] class = No 2602->2604 2606 entropy = 0.0 samples = 42 value = [42, 0] class = No 2605->2606 2607 entropy = 1.0 samples = 2 value = [1, 1] class = No 2605->2607 2609 ALCSTAT_8 <= 0.5 entropy = 0.715 samples = 178 value = [143, 35] class = No 2608->2609 2666 ECIGEV2_2.0 <= 0.5 entropy = 0.961 samples = 52 value = [32, 20] class = No 2608->2666 2610 PAR_STAT_3 <= 0.5 entropy = 0.683 samples = 171 value = [140, 31] class = No 2609->2610 2663 AHEIGHT <= 65.0 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2609->2663 2611 ASISLEEP <= 6.5 entropy = 0.989 samples = 16 value = [9, 7] class = No 2610->2611 2618 AHEARST1_4.0 <= 0.5 entropy = 0.622 samples = 155 value = [131, 24] class = No 2610->2618 2612 entropy = 0.0 samples = 5 value = [5, 0] class = No 2611->2612 2613 LOCALL1B <= 6.0 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 2611->2613 2614 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2613->2614 2615 ASICPUSE_4.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 2613->2615 2616 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2615->2616 2617 entropy = 0.0 samples = 4 value = [4, 0] class = No 2615->2617 2619 AHAYFYR_2.0 <= 0.5 entropy = 0.574 samples = 147 value = [127, 20] class = No 2618->2619 2658 DIBREL_2.0 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 2618->2658 2620 entropy = 0.0 samples = 17 value = [17, 0] class = No 2619->2620 2621 CHDEV_2.0 <= 0.5 entropy = 0.619 samples = 130 value = [110, 20] class = No 2619->2621 2622 entropy = 0.0 samples = 11 value = [11, 0] class = No 2621->2622 2623 BMI <= 1825.5 entropy = 0.653 samples = 119 value = [99, 20] class = No 2621->2623 2624 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2623->2624 2625 BMI <= 2167.5 entropy = 0.637 samples = 118 value = [99, 19] class = No 2623->2625 2626 entropy = 0.0 samples = 12 value = [12, 0] class = No 2625->2626 2627 BMI <= 2190.5 entropy = 0.678 samples = 106 value = [87, 19] class = No 2625->2627 2628 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2627->2628 2629 ASICPUSE_2.0 <= 0.5 entropy = 0.643 samples = 104 value = [87, 17] class = No 2627->2629 2630 BMI <= 2308.0 entropy = 0.695 samples = 91 value = [74, 17] class = No 2629->2630 2657 entropy = 0.0 samples = 13 value = [13, 0] class = No 2629->2657 2631 entropy = 0.0 samples = 10 value = [10, 0] class = No 2630->2631 2632 ULCEV_2.0 <= 0.5 entropy = 0.741 samples = 81 value = [64, 17] class = No 2630->2632 2633 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2632->2633 2634 BMI <= 2440.0 entropy = 0.701 samples = 79 value = [64, 15] class = No 2632->2634 2635 APLKIND_2.0 <= 0.5 entropy = 0.929 samples = 29 value = [19, 10] class = No 2634->2635 2644 CLCKTP <= 2.5 entropy = 0.469 samples = 50 value = [45, 5] class = No 2634->2644 2636 entropy = 0.0 samples = 6 value = [6, 0] class = No 2635->2636 2637 AHEIGHT <= 66.5 entropy = 0.988 samples = 23 value = [13, 10] class = No 2635->2637 2638 AHSTATYR_3.0 <= 0.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 2637->2638 2641 BMI <= 2436.5 entropy = 0.619 samples = 13 value = [11, 2] class = No 2637->2641 2639 entropy = 0.0 samples = 2 value = [2, 0] class = No 2638->2639 2640 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 2638->2640 2642 entropy = 0.0 samples = 11 value = [11, 0] class = No 2641->2642 2643 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2641->2643 2645 BEDDAYR <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 2644->2645 2650 LIVEV_2.0 <= 0.5 entropy = 0.276 samples = 42 value = [40, 2] class = No 2644->2650 2646 ALC1YR_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2645->2646 2649 entropy = 0.0 samples = 4 value = [4, 0] class = No 2645->2649 2647 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2646->2647 2648 entropy = 0.0 samples = 1 value = [1, 0] class = No 2646->2648 2651 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2650->2651 2652 WRKCATA_2.0 <= 0.5 entropy = 0.165 samples = 41 value = [40, 1] class = No 2650->2652 2653 entropy = 0.0 samples = 35 value = [35, 0] class = No 2652->2653 2654 APLKIND_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2652->2654 2655 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2654->2655 2656 entropy = 0.0 samples = 5 value = [5, 0] class = No 2654->2656 2659 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2658->2659 2660 LOCALL1B <= 3.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 2658->2660 2661 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2660->2661 2662 entropy = 0.0 samples = 4 value = [4, 0] class = No 2660->2662 2664 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2663->2664 2665 entropy = 0.0 samples = 3 value = [3, 0] class = No 2663->2665 2667 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2666->2667 2668 BMI <= 2731.5 entropy = 0.931 samples = 49 value = [32, 17] class = No 2666->2668 2669 BMI <= 2523.0 entropy = 0.974 samples = 42 value = [25, 17] class = No 2668->2669 2690 entropy = 0.0 samples = 7 value = [7, 0] class = No 2668->2690 2670 ASICNHC_3.0 <= 0.5 entropy = 0.869 samples = 31 value = [22, 9] class = No 2669->2670 2683 BMI <= 2649.5 entropy = 0.845 samples = 11 value = [3, 8] class = Yes 2669->2683 2671 JNTSYMP_2.0 <= 0.5 entropy = 0.966 samples = 23 value = [14, 9] class = No 2670->2671 2682 entropy = 0.0 samples = 8 value = [8, 0] class = No 2670->2682 2672 entropy = 0.0 samples = 6 value = [6, 0] class = No 2671->2672 2673 BMI <= 2436.0 entropy = 0.998 samples = 17 value = [8, 9] class = Yes 2671->2673 2674 LOCALL1B <= 5.5 entropy = 0.94 samples = 14 value = [5, 9] class = Yes 2673->2674 2681 entropy = 0.0 samples = 3 value = [3, 0] class = No 2673->2681 2675 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2674->2675 2676 BMI <= 2329.0 entropy = 0.991 samples = 9 value = [5, 4] class = No 2674->2676 2677 ASISTLV_4.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2676->2677 2680 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2676->2680 2678 entropy = 0.0 samples = 5 value = [5, 0] class = No 2677->2678 2679 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2677->2679 2684 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2683->2684 2685 LOCALL1B <= 7.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2683->2685 2686 DBHVCLN_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2685->2686 2689 entropy = 0.0 samples = 2 value = [2, 0] class = No 2685->2689 2687 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2686->2687 2688 entropy = 0.0 samples = 1 value = [1, 0] class = No 2686->2688 2693 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2692->2693 2694 BMI <= 3109.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 2692->2694 2695 entropy = 0.0 samples = 7 value = [7, 0] class = No 2694->2695 2696 R_MARITL_4 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 2694->2696 2697 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2696->2697 2698 entropy = 0.0 samples = 2 value = [2, 0] class = No 2696->2698 2700 WRKCATA_4.0 <= 0.5 entropy = 0.996 samples = 43 value = [20, 23] class = Yes 2699->2700 2717 MRACRPI2_2 <= 0.5 entropy = 0.851 samples = 94 value = [68, 26] class = No 2699->2717 2701 AHEIGHT <= 60.5 entropy = 0.998 samples = 38 value = [20, 18] class = No 2700->2701 2716 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2700->2716 2702 entropy = 0.0 samples = 4 value = [4, 0] class = No 2701->2702 2703 ALCSTAT_6 <= 0.5 entropy = 0.998 samples = 34 value = [16, 18] class = Yes 2701->2703 2704 BMI <= 2336.5 entropy = 0.966 samples = 23 value = [14, 9] class = No 2703->2704 2711 HIT2A_2.0 <= 0.5 entropy = 0.684 samples = 11 value = [2, 9] class = Yes 2703->2711 2705 entropy = 0.0 samples = 6 value = [6, 0] class = No 2704->2705 2706 BMI <= 2686.5 entropy = 0.998 samples = 17 value = [8, 9] class = Yes 2704->2706 2707 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 2706->2707 2708 PAR_STAT_3 <= 0.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 2706->2708 2709 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2708->2709 2710 entropy = 0.0 samples = 8 value = [8, 0] class = No 2708->2710 2712 HYPEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2711->2712 2715 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 2711->2715 2713 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2712->2713 2714 entropy = 0.0 samples = 2 value = [2, 0] class = No 2712->2714 2718 CHPAIN6M_4.0 <= 0.5 entropy = 0.802 samples = 90 value = [68, 22] class = No 2717->2718 2745 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2717->2745 2719 ALCSTAT_7 <= 0.5 entropy = 0.757 samples = 87 value = [68, 19] class = No 2718->2719 2744 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2718->2744 2720 ARTH1_2.0 <= 0.5 entropy = 0.877 samples = 64 value = [45, 19] class = No 2719->2720 2743 entropy = 0.0 samples = 23 value = [23, 0] class = No 2719->2743 2721 entropy = 0.0 samples = 10 value = [10, 0] class = No 2720->2721 2722 BMI <= 2162.5 entropy = 0.936 samples = 54 value = [35, 19] class = No 2720->2722 2723 entropy = 0.0 samples = 8 value = [8, 0] class = No 2722->2723 2724 BMI <= 2312.5 entropy = 0.978 samples = 46 value = [27, 19] class = No 2722->2724 2725 LOCALL1B <= 7.0 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 2724->2725 2730 WRKLYR4_2.0 <= 0.5 entropy = 0.909 samples = 37 value = [25, 12] class = No 2724->2730 2726 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2725->2726 2727 WRKLYR4_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2725->2727 2728 entropy = 0.0 samples = 2 value = [2, 0] class = No 2727->2728 2729 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2727->2729 2731 BMI <= 2593.0 entropy = 0.971 samples = 30 value = [18, 12] class = No 2730->2731 2742 entropy = 0.0 samples = 7 value = [7, 0] class = No 2730->2742 2732 REGION_3 <= 0.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 2731->2732 2735 BMI <= 2771.5 entropy = 0.982 samples = 19 value = [8, 11] class = Yes 2731->2735 2733 entropy = 0.0 samples = 10 value = [10, 0] class = No 2732->2733 2734 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2732->2734 2736 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2735->2736 2737 DIBREL_2.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 2735->2737 2738 SMKSTAT2_3.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 2737->2738 2741 entropy = 0.0 samples = 6 value = [6, 0] class = No 2737->2741 2739 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2738->2739 2740 entropy = 0.0 samples = 2 value = [2, 0] class = No 2738->2740 2747 CHDEV_2.0 <= 0.5 entropy = 0.652 samples = 358 value = [298, 60] class = No 2746->2747 2846 AMIGR_2.0 <= 0.5 entropy = 0.99 samples = 25 value = [14, 11] class = No 2746->2846 2748 ASIRETR_4.0 <= 0.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 2747->2748 2753 AHCNOYR2 <= 6.5 entropy = 0.627 samples = 350 value = [295, 55] class = No 2747->2753 2749 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2748->2749 2750 LOCALL1B <= 2.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 2748->2750 2751 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2750->2751 2752 entropy = 0.0 samples = 3 value = [3, 0] class = No 2750->2752 2754 BMI <= 2284.5 entropy = 0.593 samples = 335 value = [287, 48] class = No 2753->2754 2839 ALCSTAT_7 <= 0.5 entropy = 0.997 samples = 15 value = [8, 7] class = No 2753->2839 2755 CHPAIN6M_2.0 <= 0.5 entropy = 0.267 samples = 66 value = [63, 3] class = No 2754->2755 2766 HIT2A_2.0 <= 0.5 entropy = 0.651 samples = 269 value = [224, 45] class = No 2754->2766 2756 entropy = 0.0 samples = 38 value = [38, 0] class = No 2755->2756 2757 DBHVWLN_2.0 <= 0.5 entropy = 0.491 samples = 28 value = [25, 3] class = No 2755->2757 2758 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2757->2758 2759 AHCNOYR2 <= 2.5 entropy = 0.381 samples = 27 value = [25, 2] class = No 2757->2759 2760 entropy = 0.0 samples = 18 value = [18, 0] class = No 2759->2760 2761 AHEIGHT <= 63.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 2759->2761 2762 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2761->2762 2763 CLCKTP <= 3.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 2761->2763 2764 entropy = 0.0 samples = 7 value = [7, 0] class = No 2763->2764 2765 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2763->2765 2767 entropy = 0.0 samples = 27 value = [27, 0] class = No 2766->2767 2768 ASIRETR_4.0 <= 0.5 entropy = 0.693 samples = 242 value = [197, 45] class = No 2766->2768 2769 AHEIGHT <= 70.5 entropy = 0.795 samples = 150 value = [114, 36] class = No 2768->2769 2820 SUPERVIS_2.0 <= 0.5 entropy = 0.462 samples = 92 value = [83, 9] class = No 2768->2820 2770 ULCEV_2.0 <= 0.5 entropy = 0.86 samples = 113 value = [81, 32] class = No 2769->2770 2813 AMIGR_2.0 <= 0.5 entropy = 0.494 samples = 37 value = [33, 4] class = No 2769->2813 2771 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2770->2771 2772 CLCKTP <= 1.0 entropy = 0.832 samples = 110 value = [81, 29] class = No 2770->2772 2773 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2772->2773 2774 REGION_3 <= 0.5 entropy = 0.811 samples = 108 value = [81, 27] class = No 2772->2774 2775 BMI <= 2879.5 entropy = 0.706 samples = 78 value = [63, 15] class = No 2774->2775 2800 PAINLB_2.0 <= 0.5 entropy = 0.971 samples = 30 value = [18, 12] class = No 2774->2800 2776 HIT4A_2.0 <= 0.5 entropy = 0.573 samples = 59 value = [51, 8] class = No 2775->2776 2791 AVISACT_2.0 <= 0.5 entropy = 0.949 samples = 19 value = [12, 7] class = No 2775->2791 2777 SUPERVIS_2.0 <= 0.5 entropy = 0.994 samples = 11 value = [6, 5] class = No 2776->2777 2784 ASISLEEP <= 7.5 entropy = 0.337 samples = 48 value = [45, 3] class = No 2776->2784 2778 YTQU_YG1_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 2777->2778 2783 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2777->2783 2779 ASIMEDC_3.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2778->2779 2782 entropy = 0.0 samples = 5 value = [5, 0] class = No 2778->2782 2780 entropy = 0.0 samples = 1 value = [1, 0] class = No 2779->2780 2781 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2779->2781 2785 entropy = 0.0 samples = 33 value = [33, 0] class = No 2784->2785 2786 REGION_2 <= 0.5 entropy = 0.722 samples = 15 value = [12, 3] class = No 2784->2786 2787 entropy = 0.0 samples = 9 value = [9, 0] class = No 2786->2787 2788 WRKLYR4_2.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 2786->2788 2789 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2788->2789 2790 entropy = 0.0 samples = 3 value = [3, 0] class = No 2788->2790 2792 entropy = 0.0 samples = 6 value = [6, 0] class = No 2791->2792 2793 VIMGLASS_2.0 <= 0.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 2791->2793 2794 PAINECK_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 2793->2794 2799 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2793->2799 2795 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2794->2795 2796 YRSWRKPA <= 10.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 2794->2796 2797 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2796->2797 2798 entropy = 0.0 samples = 6 value = [6, 0] class = No 2796->2798 2801 entropy = 0.0 samples = 6 value = [6, 0] class = No 2800->2801 2802 AHEIGHT <= 68.5 entropy = 1.0 samples = 24 value = [12, 12] class = No 2800->2802 2803 SMKSTAT2_4.0 <= 0.5 entropy = 0.971 samples = 20 value = [12, 8] class = No 2802->2803 2812 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2802->2812 2804 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2803->2804 2805 BMI <= 2525.0 entropy = 0.874 samples = 17 value = [12, 5] class = No 2803->2805 2806 ASISLEEP <= 8.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 2805->2806 2809 ALCSTAT_2 <= 0.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 2805->2809 2807 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2806->2807 2808 entropy = 0.0 samples = 2 value = [2, 0] class = No 2806->2808 2810 entropy = 0.0 samples = 10 value = [10, 0] class = No 2809->2810 2811 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2809->2811 2814 REGION_2 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2813->2814 2817 BMI <= 2341.0 entropy = 0.196 samples = 33 value = [32, 1] class = No 2813->2817 2815 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2814->2815 2816 entropy = 0.0 samples = 1 value = [1, 0] class = No 2814->2816 2818 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2817->2818 2819 entropy = 0.0 samples = 32 value = [32, 0] class = No 2817->2819 2821 HYPEV_2.0 <= 0.5 entropy = 0.65 samples = 54 value = [45, 9] class = No 2820->2821 2838 entropy = 0.0 samples = 38 value = [38, 0] class = No 2820->2838 2822 ASRGYR_2.0 <= 0.5 entropy = 0.949 samples = 19 value = [12, 7] class = No 2821->2822 2833 HIT4A_2.0 <= 0.5 entropy = 0.316 samples = 35 value = [33, 2] class = No 2821->2833 2823 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2822->2823 2824 ASICPUSE_2.0 <= 0.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 2822->2824 2825 AHCNOYR2 <= 2.5 entropy = 0.592 samples = 14 value = [12, 2] class = No 2824->2825 2832 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2824->2832 2826 entropy = 0.0 samples = 9 value = [9, 0] class = No 2825->2826 2827 BEDDAYR <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 2825->2827 2828 AHEIGHT <= 64.0 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2827->2828 2831 entropy = 0.0 samples = 2 value = [2, 0] class = No 2827->2831 2829 entropy = 0.0 samples = 1 value = [1, 0] class = No 2828->2829 2830 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2828->2830 2834 ASISLEEP <= 6.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 2833->2834 2837 entropy = 0.0 samples = 29 value = [29, 0] class = No 2833->2837 2835 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2834->2835 2836 entropy = 0.0 samples = 4 value = [4, 0] class = No 2834->2836 2840 AHEIGHT <= 67.5 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 2839->2840 2845 entropy = 0.0 samples = 4 value = [4, 0] class = No 2839->2845 2841 YRSWRKPA <= 14.0 entropy = 0.918 samples = 6 value = [4, 2] class = No 2840->2841 2844 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2840->2844 2842 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2841->2842 2843 entropy = 0.0 samples = 4 value = [4, 0] class = No 2841->2843 2847 entropy = 0.0 samples = 6 value = [6, 0] class = No 2846->2847 2848 HIT2A_2.0 <= 0.5 entropy = 0.982 samples = 19 value = [8, 11] class = Yes 2846->2848 2849 DOINGLWA_5.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2848->2849 2852 YRSWRKPA <= 25.0 entropy = 0.779 samples = 13 value = [3, 10] class = Yes 2848->2852 2850 entropy = 0.0 samples = 5 value = [5, 0] class = No 2849->2850 2851 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2849->2851 2853 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 2852->2853 2854 SUPERVIS_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 2852->2854 2855 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2854->2855 2856 entropy = 0.0 samples = 3 value = [3, 0] class = No 2854->2856 2858 ALCSTAT_8 <= 0.5 entropy = 0.297 samples = 19 value = [18, 1] class = No 2857->2858 2861 CLCKTP <= 0.5 entropy = 0.941 samples = 260 value = [167, 93] class = No 2857->2861 2859 entropy = 0.0 samples = 18 value = [18, 0] class = No 2858->2859 2860 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2858->2860 2862 ADNLONG2_2.0 <= 0.5 entropy = 0.337 samples = 16 value = [15, 1] class = No 2861->2862 2865 JNTSYMP_2.0 <= 0.5 entropy = 0.956 samples = 244 value = [152, 92] class = No 2861->2865 2863 entropy = 0.0 samples = 15 value = [15, 0] class = No 2862->2863 2864 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2862->2864 2866 ASICPUSE_4.0 <= 0.5 entropy = 0.996 samples = 54 value = [25, 29] class = Yes 2865->2866 2885 YRSWRKPA <= 0.5 entropy = 0.917 samples = 190 value = [127, 63] class = No 2865->2885 2867 ALCSTAT_6 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 2866->2867 2870 ASICNHC_3.0 <= 0.5 entropy = 0.946 samples = 44 value = [16, 28] class = Yes 2866->2870 2868 entropy = 0.0 samples = 9 value = [9, 0] class = No 2867->2868 2869 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2867->2869 2871 DBHVCLN_2.0 <= 0.5 entropy = 0.784 samples = 30 value = [7, 23] class = Yes 2870->2871 2880 BMI <= 3460.0 entropy = 0.94 samples = 14 value = [9, 5] class = No 2870->2880 2872 DIBREL_2.0 <= 0.5 entropy = 0.934 samples = 20 value = [7, 13] class = Yes 2871->2872 2879 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 2871->2879 2873 ASISTLV_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 2872->2873 2876 ALCSTAT_8 <= 0.5 entropy = 0.619 samples = 13 value = [2, 11] class = Yes 2872->2876 2874 entropy = 0.0 samples = 5 value = [5, 0] class = No 2873->2874 2875 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2873->2875 2877 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 2876->2877 2878 entropy = 0.0 samples = 2 value = [2, 0] class = No 2876->2878 2881 REGION_2 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 2880->2881 2884 entropy = 0.0 samples = 7 value = [7, 0] class = No 2880->2884 2882 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2881->2882 2883 entropy = 0.0 samples = 2 value = [2, 0] class = No 2881->2883 2886 ASISTLV_3.0 <= 0.5 entropy = 0.454 samples = 21 value = [19, 2] class = No 2885->2886 2891 MIEV_2.0 <= 0.5 entropy = 0.943 samples = 169 value = [108, 61] class = No 2885->2891 2887 entropy = 0.0 samples = 15 value = [15, 0] class = No 2886->2887 2888 LOCALL1B <= 5.0 entropy = 0.918 samples = 6 value = [4, 2] class = No 2886->2888 2889 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2888->2889 2890 entropy = 0.0 samples = 4 value = [4, 0] class = No 2888->2890 2892 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2891->2892 2893 R_MARITL_3 <= 0.5 entropy = 0.934 samples = 166 value = [108, 58] class = No 2891->2893 2894 AHCNOYR2 <= 0.5 entropy = 0.964 samples = 139 value = [85, 54] class = No 2893->2894 2959 DOINGLWA_5.0 <= 0.5 entropy = 0.605 samples = 27 value = [23, 4] class = No 2893->2959 2895 entropy = 0.0 samples = 5 value = [5, 0] class = No 2894->2895 2896 YRSWRKPA <= 8.5 entropy = 0.973 samples = 134 value = [80, 54] class = No 2894->2896 2897 CIGAREV2_2.0 <= 0.5 entropy = 1.0 samples = 70 value = [35, 35] class = No 2896->2897 2934 BMI <= 3914.5 entropy = 0.877 samples = 64 value = [45, 19] class = No 2896->2934 2898 LOCALL1B <= 5.5 entropy = 0.764 samples = 18 value = [14, 4] class = No 2897->2898 2907 ARTH1_2.0 <= 0.5 entropy = 0.973 samples = 52 value = [21, 31] class = Yes 2897->2907 2899 ADNLONG2_1.0 <= 0.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 2898->2899 2906 entropy = 0.0 samples = 7 value = [7, 0] class = No 2898->2906 2900 BMI <= 4202.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 2899->2900 2903 CLCKTP <= 2.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2899->2903 2901 entropy = 0.0 samples = 6 value = [6, 0] class = No 2900->2901 2902 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2900->2902 2904 entropy = 0.0 samples = 1 value = [1, 0] class = No 2903->2904 2905 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2903->2905 2908 entropy = 0.0 samples = 3 value = [3, 0] class = No 2907->2908 2909 WRKCATA_2.0 <= 0.5 entropy = 0.949 samples = 49 value = [18, 31] class = Yes 2907->2909 2910 ADNLONG2_3.0 <= 0.5 entropy = 0.925 samples = 47 value = [16, 31] class = Yes 2909->2910 2933 entropy = 0.0 samples = 2 value = [2, 0] class = No 2909->2933 2911 PAINLB_2.0 <= 0.5 entropy = 0.894 samples = 45 value = [14, 31] class = Yes 2910->2911 2932 entropy = 0.0 samples = 2 value = [2, 0] class = No 2910->2932 2912 LOCALL1B <= 7.5 entropy = 1.0 samples = 16 value = [8, 8] class = No 2911->2912 2921 DIBREL_2.0 <= 0.5 entropy = 0.736 samples = 29 value = [6, 23] class = Yes 2911->2921 2913 AHEIGHT <= 65.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 2912->2913 2920 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2912->2920 2914 entropy = 0.0 samples = 5 value = [5, 0] class = No 2913->2914 2915 AMIGR_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2913->2915 2916 DIBEV1_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 2915->2916 2919 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2915->2919 2917 entropy = 0.0 samples = 3 value = [3, 0] class = No 2916->2917 2918 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2916->2918 2922 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 2921->2922 2923 ACOLD2W_2.0 <= 0.5 entropy = 0.937 samples = 17 value = [6, 11] class = Yes 2921->2923 2924 entropy = 0.0 samples = 2 value = [2, 0] class = No 2923->2924 2925 ALCSTAT_7 <= 0.5 entropy = 0.837 samples = 15 value = [4, 11] class = Yes 2923->2925 2926 ASISTLV_4.0 <= 0.5 entropy = 0.619 samples = 13 value = [2, 11] class = Yes 2925->2926 2931 entropy = 0.0 samples = 2 value = [2, 0] class = No 2925->2931 2927 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 2926->2927 2928 MRACRPI2_2 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2926->2928 2929 entropy = 0.0 samples = 2 value = [2, 0] class = No 2928->2929 2930 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2928->2930 2935 AHAYFYR_2.0 <= 0.5 entropy = 0.83 samples = 61 value = [45, 16] class = No 2934->2935 2958 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2934->2958 2936 ALCSTAT_6 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 2935->2936 2939 DBHVWLN_2.0 <= 0.5 entropy = 0.757 samples = 55 value = [43, 12] class = No 2935->2939 2937 entropy = 0.0 samples = 2 value = [2, 0] class = No 2936->2937 2938 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2936->2938 2940 entropy = 0.0 samples = 11 value = [11, 0] class = No 2939->2940 2941 BMI <= 3580.5 entropy = 0.845 samples = 44 value = [32, 12] class = No 2939->2941 2942 AASMEV_2.0 <= 0.5 entropy = 0.909 samples = 37 value = [25, 12] class = No 2941->2942 2957 entropy = 0.0 samples = 7 value = [7, 0] class = No 2941->2957 2943 entropy = 0.0 samples = 7 value = [7, 0] class = No 2942->2943 2944 AMIGR_2.0 <= 0.5 entropy = 0.971 samples = 30 value = [18, 12] class = No 2942->2944 2945 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2944->2945 2946 BMI <= 3492.5 entropy = 0.918 samples = 27 value = [18, 9] class = No 2944->2946 2947 AHEIGHT <= 60.5 entropy = 0.722 samples = 20 value = [16, 4] class = No 2946->2947 2954 DIBREL_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 2946->2954 2948 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2947->2948 2949 WRKLYR4_1.0 <= 0.5 entropy = 0.503 samples = 18 value = [16, 2] class = No 2947->2949 2950 ALCSTAT_2 <= 0.5 entropy = 0.323 samples = 17 value = [16, 1] class = No 2949->2950 2953 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2949->2953 2951 entropy = 0.0 samples = 15 value = [15, 0] class = No 2950->2951 2952 entropy = 1.0 samples = 2 value = [1, 1] class = No 2950->2952 2955 entropy = 0.0 samples = 2 value = [2, 0] class = No 2954->2955 2956 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2954->2956 2960 YRSWRKPA <= 1.5 entropy = 0.267 samples = 22 value = [21, 1] class = No 2959->2960 2963 LOCALL1B <= 7.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 2959->2963 2961 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2960->2961 2962 entropy = 0.0 samples = 21 value = [21, 0] class = No 2960->2962 2964 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2963->2964 2965 entropy = 0.0 samples = 2 value = [2, 0] class = No 2963->2965 2967 MRACRPI2_4 <= 0.5 entropy = 0.151 samples = 505 value = [494, 11] class = No 2966->2967 3002 BMI <= 2828.0 entropy = 0.453 samples = 2371 value = [2146, 225] class = No 2966->3002 2968 YRSWRKPA <= 2.5 entropy = 0.11 samples = 481 value = [474, 7] class = No 2967->2968 2991 JNTSYMP_2.0 <= 0.5 entropy = 0.65 samples = 24 value = [20, 4] class = No 2967->2991 2969 AHEIGHT <= 66.5 entropy = 0.225 samples = 165 value = [159, 6] class = No 2968->2969 2986 HYBPLEV_5.0 <= 0.5 entropy = 0.031 samples = 316 value = [315, 1] class = No 2968->2986 2970 PDSICKA_2.0 <= 0.5 entropy = 0.424 samples = 58 value = [53, 5] class = No 2969->2970 2981 CLCKTP <= 6.5 entropy = 0.076 samples = 107 value = [106, 1] class = No 2969->2981 2971 ADNLONG2_5.0 <= 0.5 entropy = 0.787 samples = 17 value = [13, 4] class = No 2970->2971 2978 AHEARST1_3.0 <= 0.5 entropy = 0.165 samples = 41 value = [40, 1] class = No 2970->2978 2972 ULCEV_2.0 <= 0.5 entropy = 0.567 samples = 15 value = [13, 2] class = No 2971->2972 2977 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2971->2977 2973 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2972->2973 2974 HYBPLEV_4.0 <= 0.5 entropy = 0.371 samples = 14 value = [13, 1] class = No 2972->2974 2975 entropy = 0.0 samples = 13 value = [13, 0] class = No 2974->2975 2976 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2974->2976 2979 entropy = 0.0 samples = 39 value = [39, 0] class = No 2978->2979 2980 entropy = 1.0 samples = 2 value = [1, 1] class = No 2978->2980 2982 entropy = 0.0 samples = 98 value = [98, 0] class = No 2981->2982 2983 HYBPLEV_2.0 <= 0.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 2981->2983 2984 entropy = 0.0 samples = 8 value = [8, 0] class = No 2983->2984 2985 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2983->2985 2987 entropy = 0.0 samples = 309 value = [309, 0] class = No 2986->2987 2988 SMKSTAT2_4.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 2986->2988 2989 entropy = 0.0 samples = 6 value = [6, 0] class = No 2988->2989 2990 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2988->2990 2992 AMDLONGR_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2991->2992 2995 ASISTLV_3.0 <= 0.5 entropy = 0.454 samples = 21 value = [19, 2] class = No 2991->2995 2993 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2992->2993 2994 entropy = 0.0 samples = 1 value = [1, 0] class = No 2992->2994 2996 entropy = 0.0 samples = 15 value = [15, 0] class = No 2995->2996 2997 R_MARITL_4 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 2995->2997 2998 ASISLEEP <= 8.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2997->2998 3001 entropy = 0.0 samples = 3 value = [3, 0] class = No 2997->3001 2999 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2998->2999 3000 entropy = 0.0 samples = 1 value = [1, 0] class = No 2998->3000 3003 ASISLEEP <= 3.5 entropy = 0.39 samples = 1827 value = [1687, 140] class = No 3002->3003 3300 VIMGLASS_2.0 <= 0.5 entropy = 0.625 samples = 544 value = [459, 85] class = No 3002->3300 3004 CHPAIN6M_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3003->3004 3007 CHLEV_2.0 <= 0.5 entropy = 0.385 samples = 1823 value = [1686, 137] class = No 3003->3007 3005 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3004->3005 3006 entropy = 0.0 samples = 1 value = [1, 0] class = No 3004->3006 3008 FLUVACYR_2.0 <= 0.5 entropy = 0.538 samples = 301 value = [264, 37] class = No 3007->3008 3075 HYPEV_2.0 <= 0.5 entropy = 0.35 samples = 1522 value = [1422, 100] class = No 3007->3075 3009 WRKCATA_4.0 <= 0.5 entropy = 0.657 samples = 171 value = [142, 29] class = No 3008->3009 3056 SUPERVIS_2.0 <= 0.5 entropy = 0.334 samples = 130 value = [122, 8] class = No 3008->3056 3010 BMI <= 2032.5 entropy = 0.695 samples = 155 value = [126, 29] class = No 3009->3010 3055 entropy = 0.0 samples = 16 value = [16, 0] class = No 3009->3055 3011 AHAYFYR_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [8, 6] class = No 3010->3011 3018 ASIMEDC_4.0 <= 0.5 entropy = 0.642 samples = 141 value = [118, 23] class = No 3010->3018 3012 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3011->3012 3013 AASMEV_2.0 <= 0.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 3011->3013 3014 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3013->3014 3015 AHCNOYR2 <= 3.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 3013->3015 3016 entropy = 0.0 samples = 7 value = [7, 0] class = No 3015->3016 3017 entropy = 1.0 samples = 2 value = [1, 1] class = No 3015->3017 3019 YRSWRKPA <= 4.5 entropy = 0.783 samples = 73 value = [56, 17] class = No 3018->3019 3044 WRKCATA_3.0 <= 0.5 entropy = 0.431 samples = 68 value = [62, 6] class = No 3018->3044 3020 entropy = 0.0 samples = 13 value = [13, 0] class = No 3019->3020 3021 PAINECK_2.0 <= 0.5 entropy = 0.86 samples = 60 value = [43, 17] class = No 3019->3021 3022 entropy = 0.0 samples = 8 value = [8, 0] class = No 3021->3022 3023 ASICNHC_4.0 <= 0.5 entropy = 0.912 samples = 52 value = [35, 17] class = No 3021->3023 3024 LOCALL1B <= 6.5 entropy = 0.746 samples = 33 value = [26, 7] class = No 3023->3024 3035 AHEIGHT <= 65.0 entropy = 0.998 samples = 19 value = [9, 10] class = Yes 3023->3035 3025 WRKLYR4_1.0 <= 0.5 entropy = 0.902 samples = 22 value = [15, 7] class = No 3024->3025 3034 entropy = 0.0 samples = 11 value = [11, 0] class = No 3024->3034 3026 AVISION_2.0 <= 0.5 entropy = 0.811 samples = 20 value = [15, 5] class = No 3025->3026 3033 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3025->3033 3027 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3026->3027 3028 ASISLEEP <= 6.5 entropy = 0.65 samples = 18 value = [15, 3] class = No 3026->3028 3029 ASISTLV_3.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 3028->3029 3032 entropy = 0.0 samples = 13 value = [13, 0] class = No 3028->3032 3030 entropy = 0.0 samples = 2 value = [2, 0] class = No 3029->3030 3031 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3029->3031 3036 entropy = 0.0 samples = 5 value = [5, 0] class = No 3035->3036 3037 REGION_4 <= 0.5 entropy = 0.863 samples = 14 value = [4, 10] class = Yes 3035->3037 3038 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 3037->3038 3039 PAR_STAT_3 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 3037->3039 3040 entropy = 0.0 samples = 3 value = [3, 0] class = No 3039->3040 3041 ASISTLV_3.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 3039->3041 3042 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3041->3042 3043 entropy = 0.0 samples = 1 value = [1, 0] class = No 3041->3043 3045 BMI <= 2669.5 entropy = 0.334 samples = 65 value = [61, 4] class = No 3044->3045 3052 ALCSTAT_5 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3044->3052 3046 ASISTLV_2.0 <= 0.5 entropy = 0.129 samples = 56 value = [55, 1] class = No 3045->3046 3049 ARTH1_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 3045->3049 3047 entropy = 0.0 samples = 54 value = [54, 0] class = No 3046->3047 3048 entropy = 1.0 samples = 2 value = [1, 1] class = No 3046->3048 3050 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3049->3050 3051 entropy = 0.0 samples = 6 value = [6, 0] class = No 3049->3051 3053 entropy = 0.0 samples = 1 value = [1, 0] class = No 3052->3053 3054 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3052->3054 3057 entropy = 0.0 samples = 50 value = [50, 0] class = No 3056->3057 3058 AWORPAY_2.0 <= 0.5 entropy = 0.469 samples = 80 value = [72, 8] class = No 3056->3058 3059 REGION_4 <= 0.5 entropy = 0.29 samples = 59 value = [56, 3] class = No 3058->3059 3068 LOCALL1B <= 4.5 entropy = 0.792 samples = 21 value = [16, 5] class = No 3058->3068 3060 entropy = 0.0 samples = 44 value = [44, 0] class = No 3059->3060 3061 CLCKTP <= 3.5 entropy = 0.722 samples = 15 value = [12, 3] class = No 3059->3061 3062 entropy = 0.0 samples = 7 value = [7, 0] class = No 3061->3062 3063 PAR_STAT_3 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 3061->3063 3064 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3063->3064 3065 BMI <= 2293.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3063->3065 3066 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3065->3066 3067 entropy = 0.0 samples = 5 value = [5, 0] class = No 3065->3067 3069 entropy = 0.0 samples = 12 value = [12, 0] class = No 3068->3069 3070 HIT4A_2.0 <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 3068->3070 3071 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3070->3071 3072 ASICPUSE_4.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 3070->3072 3073 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3072->3073 3074 entropy = 0.0 samples = 4 value = [4, 0] class = No 3072->3074 3076 ASIRETR_4.0 <= 0.5 entropy = 0.547 samples = 198 value = [173, 25] class = No 3075->3076 3123 ASICPUSE_4.0 <= 0.5 entropy = 0.314 samples = 1324 value = [1249, 75] class = No 3075->3123 3077 BMI <= 2786.0 entropy = 0.689 samples = 114 value = [93, 21] class = No 3076->3077 3112 ASISLEEP <= 8.5 entropy = 0.276 samples = 84 value = [80, 4] class = No 3076->3112 3078 AMDLONGR_2.0 <= 0.5 entropy = 0.657 samples = 112 value = [93, 19] class = No 3077->3078 3111 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3077->3111 3079 APLKIND_2.0 <= 0.5 entropy = 0.599 samples = 103 value = [88, 15] class = No 3078->3079 3106 YRSWRKPA <= 16.0 entropy = 0.991 samples = 9 value = [5, 4] class = No 3078->3106 3080 entropy = 0.0 samples = 19 value = [19, 0] class = No 3079->3080 3081 MIEV_2.0 <= 0.5 entropy = 0.677 samples = 84 value = [69, 15] class = No 3079->3081 3082 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3081->3082 3083 ALCSTAT_8 <= 0.5 entropy = 0.631 samples = 82 value = [69, 13] class = No 3081->3083 3084 AHEIGHT <= 67.5 entropy = 0.557 samples = 77 value = [67, 10] class = No 3083->3084 3103 BMI <= 2360.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 3083->3103 3085 ASISLEEP <= 7.5 entropy = 0.755 samples = 46 value = [36, 10] class = No 3084->3085 3102 entropy = 0.0 samples = 31 value = [31, 0] class = No 3084->3102 3086 AVISION_2.0 <= 0.5 entropy = 0.449 samples = 32 value = [29, 3] class = No 3085->3086 3095 AMIGR_2.0 <= 0.5 entropy = 1.0 samples = 14 value = [7, 7] class = No 3085->3095 3087 ALC1YR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3086->3087 3090 ASICNHC_2.0 <= 0.5 entropy = 0.216 samples = 29 value = [28, 1] class = No 3086->3090 3088 entropy = 0.0 samples = 1 value = [1, 0] class = No 3087->3088 3089 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3087->3089 3091 entropy = 0.0 samples = 26 value = [26, 0] class = No 3090->3091 3092 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3090->3092 3093 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3092->3093 3094 entropy = 0.0 samples = 2 value = [2, 0] class = No 3092->3094 3096 entropy = 0.0 samples = 4 value = [4, 0] class = No 3095->3096 3097 SEX_2 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 3095->3097 3098 entropy = 0.0 samples = 2 value = [2, 0] class = No 3097->3098 3099 CHDEV_2.0 <= 0.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 3097->3099 3100 entropy = 0.0 samples = 1 value = [1, 0] class = No 3099->3100 3101 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 3099->3101 3104 entropy = 0.0 samples = 2 value = [2, 0] class = No 3103->3104 3105 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3103->3105 3107 ASISLEEP <= 5.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 3106->3107 3110 entropy = 0.0 samples = 3 value = [3, 0] class = No 3106->3110 3108 entropy = 0.0 samples = 2 value = [2, 0] class = No 3107->3108 3109 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3107->3109 3113 WRKCATA_4.0 <= 0.5 entropy = 0.101 samples = 76 value = [75, 1] class = No 3112->3113 3118 LOCALL1B <= 5.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 3112->3118 3114 entropy = 0.0 samples = 71 value = [71, 0] class = No 3113->3114 3115 BMI <= 2353.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 3113->3115 3116 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3115->3116 3117 entropy = 0.0 samples = 4 value = [4, 0] class = No 3115->3117 3119 CLCKTP <= 2.0 entropy = 0.65 samples = 6 value = [5, 1] class = No 3118->3119 3122 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3118->3122 3120 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3119->3120 3121 entropy = 0.0 samples = 5 value = [5, 0] class = No 3119->3121 3124 ADNLONG2_2.0 <= 0.5 entropy = 0.159 samples = 301 value = [294, 7] class = No 3123->3124 3143 ALCSTAT_7 <= 0.5 entropy = 0.353 samples = 1023 value = [955, 68] class = No 3123->3143 3125 ASISLEEP <= 4.5 entropy = 0.042 samples = 222 value = [221, 1] class = No 3124->3125 3128 CHPAIN6M_2.0 <= 0.5 entropy = 0.388 samples = 79 value = [73, 6] class = No 3124->3128 3126 entropy = 1.0 samples = 2 value = [1, 1] class = No 3125->3126 3127 entropy = 0.0 samples = 220 value = [220, 0] class = No 3125->3127 3129 entropy = 0.0 samples = 41 value = [41, 0] class = No 3128->3129 3130 AHEIGHT <= 68.5 entropy = 0.629 samples = 38 value = [32, 6] class = No 3128->3130 3131 SUPERVIS_2.0 <= 0.5 entropy = 0.795 samples = 25 value = [19, 6] class = No 3130->3131 3142 entropy = 0.0 samples = 13 value = [13, 0] class = No 3130->3142 3132 entropy = 0.0 samples = 7 value = [7, 0] class = No 3131->3132 3133 ASISTLV_4.0 <= 0.5 entropy = 0.918 samples = 18 value = [12, 6] class = No 3131->3133 3134 AHCNOYR2 <= 2.5 entropy = 0.996 samples = 13 value = [7, 6] class = No 3133->3134 3141 entropy = 0.0 samples = 5 value = [5, 0] class = No 3133->3141 3135 YRSWRKPA <= 4.5 entropy = 0.881 samples = 10 value = [7, 3] class = No 3134->3135 3140 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3134->3140 3136 entropy = 0.0 samples = 6 value = [6, 0] class = No 3135->3136 3137 WRKLYR4_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3135->3137 3138 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3137->3138 3139 entropy = 0.0 samples = 1 value = [1, 0] class = No 3137->3139 3144 DIBPRE2_2.0 <= 0.5 entropy = 0.392 samples = 792 value = [731, 61] class = No 3143->3144 3277 HIT2A_2.0 <= 0.5 entropy = 0.196 samples = 231 value = [224, 7] class = No 3143->3277 3145 ASRGYR_2.0 <= 0.5 entropy = 0.852 samples = 18 value = [13, 5] class = No 3144->3145 3154 CIGAREV2_2.0 <= 0.5 entropy = 0.375 samples = 774 value = [718, 56] class = No 3144->3154 3146 entropy = 0.0 samples = 5 value = [5, 0] class = No 3145->3146 3147 BEDDAYR <= 1.5 entropy = 0.961 samples = 13 value = [8, 5] class = No 3145->3147 3148 LOCALL1B <= 3.0 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 3147->3148 3153 entropy = 0.0 samples = 4 value = [4, 0] class = No 3147->3153 3149 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3148->3149 3150 ASISTLV_3.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 3148->3150 3151 entropy = 0.0 samples = 4 value = [4, 0] class = No 3150->3151 3152 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3150->3152 3155 LOCALL1B <= 3.5 entropy = 0.174 samples = 154 value = [150, 4] class = No 3154->3155 3168 VIMGLASS_2.0 <= 0.5 entropy = 0.416 samples = 620 value = [568, 52] class = No 3154->3168 3156 HOURPDA_2.0 <= 0.5 entropy = 0.391 samples = 52 value = [48, 4] class = No 3155->3156 3167 entropy = 0.0 samples = 102 value = [102, 0] class = No 3155->3167 3157 entropy = 0.0 samples = 25 value = [25, 0] class = No 3156->3157 3158 ADNLONG2_2.0 <= 0.5 entropy = 0.605 samples = 27 value = [23, 4] class = No 3156->3158 3159 MRACRPI2_4 <= 0.5 entropy = 0.286 samples = 20 value = [19, 1] class = No 3158->3159 3162 AHEIGHT <= 70.0 entropy = 0.985 samples = 7 value = [4, 3] class = No 3158->3162 3160 entropy = 0.0 samples = 19 value = [19, 0] class = No 3159->3160 3161 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3159->3161 3163 AHCNOYR2 <= 5.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3162->3163 3166 entropy = 0.0 samples = 3 value = [3, 0] class = No 3162->3166 3164 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3163->3164 3165 entropy = 0.0 samples = 1 value = [1, 0] class = No 3163->3165 3169 BMI <= 2437.5 entropy = 0.492 samples = 373 value = [333, 40] class = No 3168->3169 3250 AVISION_2.0 <= 0.5 entropy = 0.28 samples = 247 value = [235, 12] class = No 3168->3250 3170 BEDDAYR <= 6.5 entropy = 0.394 samples = 257 value = [237, 20] class = No 3169->3170 3215 YRSWRKPA <= 6.5 entropy = 0.663 samples = 116 value = [96, 20] class = No 3169->3215 3171 ALC1YR_2.0 <= 0.5 entropy = 0.358 samples = 250 value = [233, 17] class = No 3170->3171 3210 LOCALL1B <= 2.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 3170->3210 3172 CHPAIN6M_4.0 <= 0.5 entropy = 0.222 samples = 168 value = [162, 6] class = No 3171->3172 3187 ASISLEEP <= 8.5 entropy = 0.569 samples = 82 value = [71, 11] class = No 3171->3187 3173 AHEIGHT <= 59.5 entropy = 0.165 samples = 164 value = [160, 4] class = No 3172->3173 3184 SMKSTAT2_4.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 3172->3184 3174 entropy = 1.0 samples = 2 value = [1, 1] class = No 3173->3174 3175 ASICNHC_3.0 <= 0.5 entropy = 0.133 samples = 162 value = [159, 3] class = No 3173->3175 3176 entropy = 0.0 samples = 112 value = [112, 0] class = No 3175->3176 3177 ACOLD2W_2.0 <= 0.5 entropy = 0.327 samples = 50 value = [47, 3] class = No 3175->3177 3178 AHEARST1_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3177->3178 3181 HIT2A_2.0 <= 0.5 entropy = 0.149 samples = 47 value = [46, 1] class = No 3177->3181 3179 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3178->3179 3180 entropy = 0.0 samples = 1 value = [1, 0] class = No 3178->3180 3182 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3181->3182 3183 entropy = 0.0 samples = 46 value = [46, 0] class = No 3181->3183 3185 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3184->3185 3186 entropy = 0.0 samples = 2 value = [2, 0] class = No 3184->3186 3188 AHEIGHT <= 66.5 entropy = 0.477 samples = 78 value = [70, 8] class = No 3187->3188 3207 AHCNOYR2 <= 2.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3187->3207 3189 ASIRETR_3.0 <= 0.5 entropy = 0.235 samples = 52 value = [50, 2] class = No 3188->3189 3196 SEX_2 <= 0.5 entropy = 0.779 samples = 26 value = [20, 6] class = No 3188->3196 3190 entropy = 0.0 samples = 42 value = [42, 0] class = No 3189->3190 3191 YRSWRKPA <= 3.5 entropy = 0.722 samples = 10 value = [8, 2] class = No 3189->3191 3192 MRACRPI2_4 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3191->3192 3195 entropy = 0.0 samples = 7 value = [7, 0] class = No 3191->3195 3193 entropy = 0.0 samples = 1 value = [1, 0] class = No 3192->3193 3194 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3192->3194 3197 entropy = 0.0 samples = 10 value = [10, 0] class = No 3196->3197 3198 REGION_3 <= 0.5 entropy = 0.954 samples = 16 value = [10, 6] class = No 3196->3198 3199 HOURPDA_2.0 <= 0.5 entropy = 0.779 samples = 13 value = [10, 3] class = No 3198->3199 3206 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3198->3206 3200 entropy = 0.0 samples = 7 value = [7, 0] class = No 3199->3200 3201 LOCALL1B <= 4.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3199->3201 3202 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3201->3202 3203 WRKLYR4_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 3201->3203 3204 entropy = 0.0 samples = 3 value = [3, 0] class = No 3203->3204 3205 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3203->3205 3208 entropy = 0.0 samples = 1 value = [1, 0] class = No 3207->3208 3209 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3207->3209 3211 entropy = 0.0 samples = 3 value = [3, 0] class = No 3210->3211 3212 WRKCATA_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3210->3212 3213 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3212->3213 3214 entropy = 0.0 samples = 1 value = [1, 0] class = No 3212->3214 3216 AHAYFYR_2.0 <= 0.5 entropy = 0.426 samples = 69 value = [63, 6] class = No 3215->3216 3231 ASIMEDC_2.0 <= 0.5 entropy = 0.879 samples = 47 value = [33, 14] class = No 3215->3231 3217 AVISACT_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3216->3217 3220 YRSWRKPA <= 2.5 entropy = 0.33 samples = 66 value = [62, 4] class = No 3216->3220 3218 entropy = 0.0 samples = 1 value = [1, 0] class = No 3217->3218 3219 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3217->3219 3221 LOCALL1B <= 8.5 entropy = 0.503 samples = 36 value = [32, 4] class = No 3220->3221 3230 entropy = 0.0 samples = 30 value = [30, 0] class = No 3220->3230 3222 BMI <= 2461.0 entropy = 0.422 samples = 35 value = [32, 3] class = No 3221->3222 3229 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3221->3229 3223 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3222->3223 3224 AMIGR_2.0 <= 0.5 entropy = 0.323 samples = 34 value = [32, 2] class = No 3222->3224 3225 AHCNOYR2 <= 1.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 3224->3225 3228 entropy = 0.0 samples = 27 value = [27, 0] class = No 3224->3228 3226 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3225->3226 3227 entropy = 0.0 samples = 5 value = [5, 0] class = No 3225->3227 3232 BMI <= 2571.0 entropy = 0.964 samples = 36 value = [22, 14] class = No 3231->3232 3249 entropy = 0.0 samples = 11 value = [11, 0] class = No 3231->3249 3233 AHCNOYR2 <= 2.5 entropy = 0.977 samples = 17 value = [7, 10] class = Yes 3232->3233 3242 LOCALL1B <= 3.5 entropy = 0.742 samples = 19 value = [15, 4] class = No 3232->3242 3234 HIT2A_2.0 <= 0.5 entropy = 0.503 samples = 9 value = [1, 8] class = Yes 3233->3234 3237 LOCALL1B <= 4.0 entropy = 0.811 samples = 8 value = [6, 2] class = No 3233->3237 3235 entropy = 0.0 samples = 1 value = [1, 0] class = No 3234->3235 3236 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 3234->3236 3238 ASRGYR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3237->3238 3241 entropy = 0.0 samples = 5 value = [5, 0] class = No 3237->3241 3239 entropy = 0.0 samples = 1 value = [1, 0] class = No 3238->3239 3240 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3238->3240 3243 entropy = 0.0 samples = 7 value = [7, 0] class = No 3242->3243 3244 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 3242->3244 3245 entropy = 0.0 samples = 5 value = [5, 0] class = No 3244->3245 3246 DIBREL_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 3244->3246 3247 entropy = 0.0 samples = 3 value = [3, 0] class = No 3246->3247 3248 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3246->3248 3251 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3250->3251 3252 SMKSTAT2_4.0 <= 0.5 entropy = 0.246 samples = 245 value = [235, 10] class = No 3250->3252 3253 BEDDAYR <= 2.5 entropy = 0.52 samples = 60 value = [53, 7] class = No 3252->3253 3266 LOCALL1B <= 6.5 entropy = 0.12 samples = 185 value = [182, 3] class = No 3252->3266 3254 SEX_2 <= 0.5 entropy = 0.31 samples = 54 value = [51, 3] class = No 3253->3254 3263 REGION_2 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 3253->3263 3255 CLCKTP <= 3.5 entropy = 0.696 samples = 16 value = [13, 3] class = No 3254->3255 3262 entropy = 0.0 samples = 38 value = [38, 0] class = No 3254->3262 3256 entropy = 0.0 samples = 10 value = [10, 0] class = No 3255->3256 3257 ASICNHC_4.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3255->3257 3258 entropy = 0.0 samples = 2 value = [2, 0] class = No 3257->3258 3259 SMKSTAT2_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3257->3259 3260 entropy = 0.0 samples = 1 value = [1, 0] class = No 3259->3260 3261 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3259->3261 3264 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3263->3264 3265 entropy = 0.0 samples = 2 value = [2, 0] class = No 3263->3265 3267 entropy = 0.0 samples = 135 value = [135, 0] class = No 3266->3267 3268 YRSWRKPA <= 21.5 entropy = 0.327 samples = 50 value = [47, 3] class = No 3266->3268 3269 HIT2A_2.0 <= 0.5 entropy = 0.246 samples = 49 value = [47, 2] class = No 3268->3269 3276 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3268->3276 3270 AHEIGHT <= 66.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 3269->3270 3275 entropy = 0.0 samples = 41 value = [41, 0] class = No 3269->3275 3271 ADNLONG2_1.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3270->3271 3274 entropy = 0.0 samples = 5 value = [5, 0] class = No 3270->3274 3272 entropy = 0.0 samples = 1 value = [1, 0] class = No 3271->3272 3273 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3271->3273 3278 CLCKTP <= 3.5 entropy = 0.567 samples = 30 value = [26, 4] class = No 3277->3278 3287 VIMGLASS_2.0 <= 0.5 entropy = 0.112 samples = 201 value = [198, 3] class = No 3277->3287 3279 ASICNHC_4.0 <= 0.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 3278->3279 3286 entropy = 0.0 samples = 14 value = [14, 0] class = No 3278->3286 3280 entropy = 0.0 samples = 6 value = [6, 0] class = No 3279->3280 3281 ASISTLV_4.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 3279->3281 3282 AVISION_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 3281->3282 3285 entropy = 0.0 samples = 5 value = [5, 0] class = No 3281->3285 3283 entropy = 0.0 samples = 1 value = [1, 0] class = No 3282->3283 3284 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3282->3284 3288 CHPAIN6M_2.0 <= 0.5 entropy = 0.183 samples = 108 value = [105, 3] class = No 3287->3288 3299 entropy = 0.0 samples = 93 value = [93, 0] class = No 3287->3299 3289 AHEIGHT <= 70.5 entropy = 0.318 samples = 52 value = [49, 3] class = No 3288->3289 3298 entropy = 0.0 samples = 56 value = [56, 0] class = No 3288->3298 3290 AHEIGHT <= 66.5 entropy = 0.48 samples = 29 value = [26, 3] class = No 3289->3290 3297 entropy = 0.0 samples = 23 value = [23, 0] class = No 3289->3297 3291 entropy = 0.0 samples = 18 value = [18, 0] class = No 3290->3291 3292 LOCALL1B <= 5.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 3290->3292 3293 AHEIGHT <= 67.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 3292->3293 3296 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3292->3296 3294 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3293->3294 3295 entropy = 0.0 samples = 8 value = [8, 0] class = No 3293->3295 3301 DBHVCLN_2.0 <= 0.5 entropy = 0.722 samples = 345 value = [276, 69] class = No 3300->3301 3396 YRSWRKPA <= 6.5 entropy = 0.404 samples = 199 value = [183, 16] class = No 3300->3396 3302 YRSWRKPA <= 21.5 entropy = 0.883 samples = 93 value = [65, 28] class = No 3301->3302 3333 CIGAREV2_2.0 <= 0.5 entropy = 0.641 samples = 252 value = [211, 41] class = No 3301->3333 3303 AASMEV_2.0 <= 0.5 entropy = 0.953 samples = 75 value = [47, 28] class = No 3302->3303 3332 entropy = 0.0 samples = 18 value = [18, 0] class = No 3302->3332 3304 BMI <= 3040.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 3303->3304 3309 SMKSTAT2_4.0 <= 0.5 entropy = 0.89 samples = 65 value = [45, 20] class = No 3303->3309 3305 ALCSTAT_8 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3304->3305 3308 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 3304->3308 3306 entropy = 0.0 samples = 2 value = [2, 0] class = No 3305->3306 3307 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3305->3307 3310 ASIMEDC_3.0 <= 0.5 entropy = 0.454 samples = 21 value = [19, 2] class = No 3309->3310 3315 HIT1A_2.0 <= 0.5 entropy = 0.976 samples = 44 value = [26, 18] class = No 3309->3315 3311 entropy = 0.0 samples = 16 value = [16, 0] class = No 3310->3311 3312 REGION_3 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 3310->3312 3313 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3312->3313 3314 entropy = 0.0 samples = 3 value = [3, 0] class = No 3312->3314 3316 AWORPAY_3.0 <= 0.5 entropy = 0.991 samples = 27 value = [12, 15] class = Yes 3315->3316 3327 REGION_3 <= 0.5 entropy = 0.672 samples = 17 value = [14, 3] class = No 3315->3327 3317 CLCKTP <= 3.5 entropy = 0.722 samples = 15 value = [3, 12] class = Yes 3316->3317 3322 AHEIGHT <= 69.5 entropy = 0.811 samples = 12 value = [9, 3] class = No 3316->3322 3318 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 3317->3318 3319 CHPAIN6M_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 3317->3319 3320 entropy = 0.0 samples = 3 value = [3, 0] class = No 3319->3320 3321 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3319->3321 3323 entropy = 0.0 samples = 8 value = [8, 0] class = No 3322->3323 3324 ASISTLV_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3322->3324 3325 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3324->3325 3326 entropy = 0.0 samples = 1 value = [1, 0] class = No 3324->3326 3328 entropy = 0.0 samples = 11 value = [11, 0] class = No 3327->3328 3329 FLUVACYR_2.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3327->3329 3330 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3329->3330 3331 entropy = 0.0 samples = 3 value = [3, 0] class = No 3329->3331 3334 YRSWRKPA <= 11.5 entropy = 0.89 samples = 65 value = [45, 20] class = No 3333->3334 3355 HIT3A_2.0 <= 0.5 entropy = 0.507 samples = 187 value = [166, 21] class = No 3333->3355 3335 ALCSTAT_8 <= 0.5 entropy = 0.485 samples = 38 value = [34, 4] class = No 3334->3335 3344 BMI <= 3069.5 entropy = 0.975 samples = 27 value = [11, 16] class = Yes 3334->3344 3336 BMI <= 3648.5 entropy = 0.201 samples = 32 value = [31, 1] class = No 3335->3336 3339 SMKSTAT2_3.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3335->3339 3337 entropy = 0.0 samples = 30 value = [30, 0] class = No 3336->3337 3338 entropy = 1.0 samples = 2 value = [1, 1] class = No 3336->3338 3340 ASIMEDC_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 3339->3340 3343 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3339->3343 3341 entropy = 0.0 samples = 3 value = [3, 0] class = No 3340->3341 3342 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3340->3342 3345 ALCSTAT_7 <= 0.5 entropy = 0.619 samples = 13 value = [2, 11] class = Yes 3344->3345 3350 YRSWRKPA <= 16.5 entropy = 0.94 samples = 14 value = [9, 5] class = No 3344->3350 3346 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 3345->3346 3347 ASICNHC_4.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 3345->3347 3348 entropy = 0.0 samples = 2 value = [2, 0] class = No 3347->3348 3349 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3347->3349 3351 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3350->3351 3352 HIT4A_2.0 <= 0.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 3350->3352 3353 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3352->3353 3354 entropy = 0.0 samples = 9 value = [9, 0] class = No 3352->3354 3356 YRSWRKPA <= 8.5 entropy = 0.918 samples = 21 value = [14, 7] class = No 3355->3356 3367 YRSWRKPA <= 18.5 entropy = 0.417 samples = 166 value = [152, 14] class = No 3355->3367 3357 ALCSTAT_6 <= 0.5 entropy = 0.696 samples = 16 value = [13, 3] class = No 3356->3357 3364 LOCALL1B <= 8.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 3356->3364 3358 entropy = 0.0 samples = 10 value = [10, 0] class = No 3357->3358 3359 ASIRETR_4.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3357->3359 3360 LOCALL1B <= 7.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3359->3360 3363 entropy = 0.0 samples = 2 value = [2, 0] class = No 3359->3363 3361 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3360->3361 3362 entropy = 0.0 samples = 1 value = [1, 0] class = No 3360->3362 3365 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3364->3365 3366 entropy = 0.0 samples = 1 value = [1, 0] class = No 3364->3366 3368 AHEIGHT <= 66.5 entropy = 0.534 samples = 115 value = [101, 14] class = No 3367->3368 3395 entropy = 0.0 samples = 51 value = [51, 0] class = No 3367->3395 3369 WRKLYR4_2.0 <= 0.5 entropy = 0.684 samples = 66 value = [54, 12] class = No 3368->3369 3390 LOCALL1B <= 1.5 entropy = 0.246 samples = 49 value = [47, 2] class = No 3368->3390 3370 ALC1YR_2.0 <= 0.5 entropy = 0.523 samples = 51 value = [45, 6] class = No 3369->3370 3383 ALC1YR_2.0 <= 0.5 entropy = 0.971 samples = 15 value = [9, 6] class = No 3369->3383 3371 BMI <= 3224.0 entropy = 0.696 samples = 32 value = [26, 6] class = No 3370->3371 3382 entropy = 0.0 samples = 19 value = [19, 0] class = No 3370->3382 3372 R_MARITL_3 <= 0.5 entropy = 0.402 samples = 25 value = [23, 2] class = No 3371->3372 3377 YRSWRKPA <= 2.0 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 3371->3377 3373 entropy = 0.0 samples = 19 value = [19, 0] class = No 3372->3373 3374 AHEARST1_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 3372->3374 3375 entropy = 0.0 samples = 4 value = [4, 0] class = No 3374->3375 3376 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3374->3376 3378 SINYR_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 3377->3378 3381 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3377->3381 3379 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3378->3379 3380 entropy = 0.0 samples = 3 value = [3, 0] class = No 3378->3380 3384 HIT2A_2.0 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 3383->3384 3387 AMDLONGR_1.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 3383->3387 3385 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3384->3385 3386 entropy = 0.0 samples = 7 value = [7, 0] class = No 3384->3386 3388 entropy = 0.0 samples = 2 value = [2, 0] class = No 3387->3388 3389 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 3387->3389 3391 JNTSYMP_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 3390->3391 3394 entropy = 0.0 samples = 45 value = [45, 0] class = No 3390->3394 3392 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3391->3392 3393 entropy = 0.0 samples = 2 value = [2, 0] class = No 3391->3393 3397 CIGAREV2_2.0 <= 0.5 entropy = 0.222 samples = 112 value = [108, 4] class = No 3396->3397 3412 BMI <= 3229.5 entropy = 0.579 samples = 87 value = [75, 12] class = No 3396->3412 3398 CHPAIN6M_2.0 <= 0.5 entropy = 0.485 samples = 38 value = [34, 4] class = No 3397->3398 3411 entropy = 0.0 samples = 74 value = [74, 0] class = No 3397->3411 3399 BEDDAYR <= 0.5 entropy = 0.742 samples = 19 value = [15, 4] class = No 3398->3399 3410 entropy = 0.0 samples = 19 value = [19, 0] class = No 3398->3410 3400 AMDLONGR_2.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 3399->3400 3409 entropy = 0.0 samples = 7 value = [7, 0] class = No 3399->3409 3401 BMI <= 3263.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 3400->3401 3408 entropy = 0.0 samples = 4 value = [4, 0] class = No 3400->3408 3402 HOURPDA_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 3401->3402 3407 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3401->3407 3403 entropy = 0.0 samples = 3 value = [3, 0] class = No 3402->3403 3404 ASICNHC_3.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3402->3404 3405 entropy = 0.0 samples = 1 value = [1, 0] class = No 3404->3405 3406 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3404->3406 3413 DIBREL_2.0 <= 0.5 entropy = 0.362 samples = 58 value = [54, 4] class = No 3412->3413 3422 ASISTLV_3.0 <= 0.5 entropy = 0.85 samples = 29 value = [21, 8] class = No 3412->3422 3414 BMI <= 3008.5 entropy = 0.787 samples = 17 value = [13, 4] class = No 3413->3414 3421 entropy = 0.0 samples = 41 value = [41, 0] class = No 3413->3421 3415 ASICPUSE_4.0 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 3414->3415 3420 entropy = 0.0 samples = 9 value = [9, 0] class = No 3414->3420 3416 entropy = 0.0 samples = 3 value = [3, 0] class = No 3415->3416 3417 CHPAIN6M_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 3415->3417 3418 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3417->3418 3419 entropy = 0.0 samples = 1 value = [1, 0] class = No 3417->3419 3423 HOURPDA_2.0 <= 0.5 entropy = 0.559 samples = 23 value = [20, 3] class = No 3422->3423 3430 DIBEV1_3.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 3422->3430 3424 entropy = 0.0 samples = 15 value = [15, 0] class = No 3423->3424 3425 SMKSTAT2_4.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 3423->3425 3426 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3425->3426 3427 ASICPUSE_4.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3425->3427 3428 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3427->3428 3429 entropy = 0.0 samples = 5 value = [5, 0] class = No 3427->3429 3431 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 3430->3431 3432 entropy = 0.0 samples = 1 value = [1, 0] class = No 3430->3432
In [104]:
system(dot -Tpng tree.dot -o dtree.png)
Out[104]:
['dot: graph is too large for cairo-renderer bitmaps. Scaling by 0.447679 to fit']
In [105]:
from IPython.display import Image
Image(filename='dtree.png', width=800)
Out[105]:
In [106]:
########################################################################################

#Feature Selection


########################################################################################
In [107]:
#Select the top 30% of the most important features, using a chi2 test
fs = feature_selection.SelectPercentile(feature_selection.chi2, percentile=30)
X_train_fs = fs.fit_transform(X_train, y_train)
In [108]:
np.set_printoptions(suppress=True, precision=2, linewidth=320)
print fs.get_support()
print fs.scores_
[False False False  True False False False False False False False False False False False  True False False False False False False False  True False  True  True  True False False False  True False False False False False False False  True  True  True  True False  True  True  True False False False False False False
  True  True False  True False False False False False False  True False False False False False  True False False  True  True  True False  True False False False False False False  True False False False False False False False False False False False False False False  True  True  True  True  True  True False False
 False  True False False False False  True False  True  True False  True  True False  True  True False  True False False False False False False False False False False  True False False  True  True False  True False]
[    10.72      1.68      9.72     42.97     20.42      0.02      7.79      9.57     12.92      0.1       0.05      8.28      1.46      0.07      3.96     24.44      1.4       2.26      9.69      4.99     11.86      0.27      2.46     27.11      3.43     37.76    174.82    133.36     13.09      8.47     16.18
    156.37      3.78      1.79      1.22      1.21      4.47      2.17      1.06    948.91     80.2     233.95    260.41     10.9      52.58    164.75     40.41      0.2       6.38     18.85      1.7       0.32      0.82    104.42     83.61     16.39     55.63      1.48      7.44      0.22      1.2      19.82
     20.39     27.81      5.89      5.94      8.21      0.37      0.28     98.65     14.61      7.42     41.47    113.34     48.25     18.63    180.22      0.26      5.92      4.84      0.78      1.09      0.52     21.71      6.3      11.64      6.77      0.57     19.69     11.08      9.19     15.04      0.01
      0.14      0.08      0.21      0.9       6.93     66.32     38.1     131.33     89.32     25.55     27.68      9.85      6.08     13.66     40.24      0.31      1.94      0.03      0.       21.05      6.23     55.6      26.7       2.44     48.33     43.23      2.72     72.05     33.71      0.09     30.25
      0.11      7.04     13.33     12.16     17.41      1.55     12.43      0.11      3.35      0.64    383.87      0.47      7.69 132452.6    5547.65     14.53    619.91     11.15]
In [109]:
X.columns.values
Out[109]:
array(['SEX_2', 'R_MARITL_2', 'R_MARITL_3', 'R_MARITL_4', 'MRACRPI2_2', 'MRACRPI2_3', 'MRACRPI2_4', 'REGION_2', 'REGION_3', 'REGION_4', 'PAR_STAT_2', 'PAR_STAT_3', 'DOINGLWA_2.0', 'DOINGLWA_3.0', 'DOINGLWA_4.0', 'DOINGLWA_5.0', 'SUPERVIS_2.0', 'WRKCATA_2.0', 'WRKCATA_3.0', 'WRKCATA_4.0', 'WRKCATA_5.0', 'WRKCATA_6.0',
       'HOURPDA_2.0', 'PDSICKA_2.0', 'WRKLYR4_1.0', 'WRKLYR4_2.0', 'HYPEV_2.0', 'HYBPLEV_2.0', 'HYBPLEV_3.0', 'HYBPLEV_4.0', 'HYBPLEV_5.0', 'CHLEV_2.0', 'CHDEV_2.0', 'MIEV_2.0', 'STREV_2.0', 'COPDEV_2.0', 'AASMEV_2.0', 'ULCEV_2.0', 'CANEV_2.0', 'DBHVCLY_2.0', 'DBHVWLY_2.0', 'DBHVPAN_2.0', 'DBHVCLN_2.0', 'DBHVWLN_2.0',
       'DIBREL_2.0', 'DIBEV1_3.0', 'DIBPRE2_2.0', 'EPILEP1_2.0', 'AHAYFYR_2.0', 'SINYR_2.0', 'CBRCHYR_2.0', 'KIDWKYR_2.0', 'LIVYR_2.0', 'JNTSYMP_2.0', 'ARTH1_2.0', 'PAINECK_2.0', 'PAINLB_2.0', 'PAINFACE_2.0', 'AMIGR_2.0', 'ACOLD2W_2.0', 'AINTIL2W_2.0', 'AHEARST1_2.0', 'AHEARST1_3.0', 'AHEARST1_4.0', 'AHEARST1_5.0',
       'AHEARST1_6.0', 'AVISION_2.0', 'VIM_GLEV_2.0', 'VIM_MDEV_2.0', 'VIMGLASS_2.0', 'AVISACT_2.0', 'CHPAIN6M_2.0', 'CHPAIN6M_3.0', 'CHPAIN6M_4.0', 'AHSTATYR_2.0', 'AHSTATYR_3.0', 'FLA1AR_2', 'FLA1AR_3', 'SPECEQ_2.0', 'ALC1YR_2.0', 'CIGAREV2_2.0', 'ECIGEV2_2.0', 'SMKSTAT2_2.0', 'SMKSTAT2_3.0', 'SMKSTAT2_4.0',
       'APLKIND_2.0', 'APLKIND_3.0', 'APLKIND_4.0', 'APLKIND_5.0', 'APLKIND_6.0', 'AWORPAY_2.0', 'AWORPAY_3.0', 'ADNLONG2_1.0', 'ADNLONG2_2.0', 'ADNLONG2_3.0', 'ADNLONG2_4.0', 'ADNLONG2_5.0', 'ASRGYR_2.0', 'AMDLONGR_1.0', 'AMDLONGR_2.0', 'AMDLONGR_3.0', 'AMDLONGR_4.0', 'AMDLONGR_5.0', 'HIT1A_2.0', 'HIT2A_2.0',
       'HIT3A_2.0', 'HIT4A_2.0', 'FLUVACYR_2.0', 'LIVEV_2.0', 'ASICPUSE_2.0', 'ASICPUSE_3.0', 'ASICPUSE_4.0', 'ASIRETR_2.0', 'ASIRETR_3.0', 'ASIRETR_4.0', 'ASIMEDC_2.0', 'ASIMEDC_3.0', 'ASIMEDC_4.0', 'ASISTLV_2.0', 'ASISTLV_3.0', 'ASISTLV_4.0', 'ASICNHC_2.0', 'ASICNHC_3.0', 'ASICNHC_4.0', 'AWEBUSE_2.0',
       'YTQU_YG1_2.0', 'ALCSTAT_2', 'ALCSTAT_3', 'ALCSTAT_5', 'ALCSTAT_6', 'ALCSTAT_7', 'ALCSTAT_8', 'ALCSTAT_9', 'ALCSTAT_10', 'YRSWRKPA', 'ASISLEEP', 'AHEIGHT', 'BMI', 'BEDDAYR', 'CLCKTP', 'AHCNOYR2', 'LOCALL1B'], dtype=object)
In [110]:
col_fs = X.columns[fs.get_support()].values
print X.columns[fs.get_support()].values
['R_MARITL_4' 'DOINGLWA_5.0' 'PDSICKA_2.0' 'WRKLYR4_2.0' 'HYPEV_2.0' 'HYBPLEV_2.0' 'CHLEV_2.0' 'DBHVCLY_2.0' 'DBHVWLY_2.0' 'DBHVPAN_2.0' 'DBHVCLN_2.0' 'DIBREL_2.0' 'DIBEV1_3.0' 'DIBPRE2_2.0' 'JNTSYMP_2.0' 'ARTH1_2.0' 'PAINLB_2.0' 'AHEARST1_4.0' 'VIMGLASS_2.0' 'CHPAIN6M_3.0' 'CHPAIN6M_4.0' 'AHSTATYR_2.0' 'FLA1AR_2'
 'SMKSTAT2_3.0' 'AMDLONGR_1.0' 'AMDLONGR_2.0' 'AMDLONGR_3.0' 'AMDLONGR_4.0' 'AMDLONGR_5.0' 'HIT1A_2.0' 'FLUVACYR_2.0' 'ASIRETR_2.0' 'ASIRETR_4.0' 'ASIMEDC_2.0' 'ASIMEDC_4.0' 'ASISTLV_2.0' 'ASISTLV_4.0' 'ASICNHC_2.0' 'ASICNHC_4.0' 'YRSWRKPA' 'BMI' 'BEDDAYR' 'AHCNOYR2']
In [111]:
for i in range(len(X.columns.values)):
    if fs.get_support()[i]:
        print X.columns.values[i],'\t', fs.scores_[i] 
R_MARITL_4 	42.97152965573381
DOINGLWA_5.0 	24.440677734009945
PDSICKA_2.0 	27.10800102976878
WRKLYR4_2.0 	37.76499086934696
HYPEV_2.0 	174.81754238183038
HYBPLEV_2.0 	133.3646814616467
CHLEV_2.0 	156.37477740755534
DBHVCLY_2.0 	948.91334245696
DBHVWLY_2.0 	80.20430711762559
DBHVPAN_2.0 	233.9509717959108
DBHVCLN_2.0 	260.4055529331171
DIBREL_2.0 	52.58443908027876
DIBEV1_3.0 	164.75186542982306
DIBPRE2_2.0 	40.411086027522884
JNTSYMP_2.0 	104.42454178999881
ARTH1_2.0 	83.6062555320664
PAINLB_2.0 	55.630962083655746
AHEARST1_4.0 	27.81375394162351
VIMGLASS_2.0 	98.653988185113
CHPAIN6M_3.0 	41.46666230317362
CHPAIN6M_4.0 	113.34459081440757
AHSTATYR_2.0 	48.25193656407255
FLA1AR_2 	180.22167830918744
SMKSTAT2_3.0 	21.71492487041027
AMDLONGR_1.0 	66.3231659504418
AMDLONGR_2.0 	38.10360226780435
AMDLONGR_3.0 	131.32662236622852
AMDLONGR_4.0 	89.3167521015692
AMDLONGR_5.0 	25.547233725732838
HIT1A_2.0 	27.68184610025459
FLUVACYR_2.0 	40.24264705761122
ASIRETR_2.0 	21.052242302414538
ASIRETR_4.0 	55.59611012637859
ASIMEDC_2.0 	26.700352963740706
ASIMEDC_4.0 	48.33124227740484
ASISTLV_2.0 	43.22566011238222
ASISTLV_4.0 	72.04598454087514
ASICNHC_2.0 	33.714098390376236
ASICNHC_4.0 	30.2535777501622
YRSWRKPA 	383.87234485952877
BMI 	132452.60155182699
BEDDAYR 	5547.650450683772
AHCNOYR2 	619.9089219391334
In [112]:
print X_train_fs
[[   0.    0.    0. ... 3662.    0.    1.]
 [   0.    0.    0. ... 2711.    0.    3.]
 [   0.    1.    1. ... 3070.    0.    1.]
 ...
 [   1.    1.    0. ... 2206.    1.    1.]
 [   1.    0.    0. ... 1892.    5.    3.]
 [   0.    0.    0. ... 2510.    0.    1.]]
In [113]:
dt = tree.DecisionTreeClassifier(criterion='entropy')
dt.fit(X_train_fs, y_train)
X_test_fs = fs.transform(X_test)
measure_performance(X_test_fs, y_test, dt, show_confussion_matrix=False, show_classification_report=True)
Accuracy:0.706 

Classification report
             precision    recall  f1-score   support

          0       0.79      0.77      0.78      2140
          1       0.55      0.57      0.56      1043

avg / total       0.71      0.71      0.71      3183


In [114]:
#export_graphviz(dt,out_file='tree2.dot', feature_names=X_train_fs.columns, class_names=["No","Yes"])
export_graphviz(dt,out_file='tree2.dot', feature_names=col_fs, class_names=["No","Yes"])

with open("tree2.dot") as f:
    dot_graph = f.read()
graphviz.Source(dot_graph)
Out[114]:
Tree 0 DBHVCLY_2.0 <= 0.5 entropy = 0.916 samples = 12730 value = [8520, 4210] class = No 1 BMI <= 2815.5 entropy = 0.77 samples = 3188 value = [718, 2470] class = Yes 0->1 True 1258 FLA1AR_2 <= 0.5 entropy = 0.685 samples = 9542 value = [7802, 1740] class = No 0->1258 False 2 DBHVPAN_2.0 <= 0.5 entropy = 0.916 samples = 1032 value = [342, 690] class = Yes 1->2 495 DBHVWLY_2.0 <= 0.5 entropy = 0.668 samples = 2156 value = [376, 1780] class = Yes 1->495 3 DBHVCLN_2.0 <= 0.5 entropy = 0.854 samples = 709 value = [198, 511] class = Yes 2->3 338 ASISTLV_4.0 <= 0.5 entropy = 0.992 samples = 323 value = [144, 179] class = Yes 2->338 4 AMDLONGR_1.0 <= 0.5 entropy = 0.823 samples = 613 value = [158, 455] class = Yes 3->4 285 PAINLB_2.0 <= 0.5 entropy = 0.98 samples = 96 value = [40, 56] class = Yes 3->285 5 HYBPLEV_2.0 <= 0.5 entropy = 0.96 samples = 94 value = [36, 58] class = Yes 4->5 52 ASICNHC_4.0 <= 0.5 entropy = 0.787 samples = 519 value = [122, 397] class = Yes 4->52 6 BEDDAYR <= 0.5 entropy = 0.976 samples = 88 value = [36, 52] class = Yes 5->6 51 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 5->51 7 BMI <= 2783.0 entropy = 0.998 samples = 63 value = [30, 33] class = Yes 6->7 38 YRSWRKPA <= 10.5 entropy = 0.795 samples = 25 value = [6, 19] class = Yes 6->38 8 BMI <= 2505.0 entropy = 0.99 samples = 59 value = [26, 33] class = Yes 7->8 37 entropy = 0.0 samples = 4 value = [4, 0] class = No 7->37 9 AHSTATYR_2.0 <= 0.5 entropy = 0.831 samples = 19 value = [5, 14] class = Yes 8->9 16 BMI <= 2508.5 entropy = 0.998 samples = 40 value = [21, 19] class = No 8->16 10 ASISTLV_2.0 <= 0.5 entropy = 0.672 samples = 17 value = [3, 14] class = Yes 9->10 15 entropy = 0.0 samples = 2 value = [2, 0] class = No 9->15 11 BMI <= 1986.5 entropy = 0.353 samples = 15 value = [1, 14] class = Yes 10->11 14 entropy = 0.0 samples = 2 value = [2, 0] class = No 10->14 12 entropy = 0.0 samples = 1 value = [1, 0] class = No 11->12 13 entropy = 0.0 samples = 14 value = [0, 14] class = Yes 11->13 17 entropy = 0.0 samples = 4 value = [4, 0] class = No 16->17 18 PAINLB_2.0 <= 0.5 entropy = 0.998 samples = 36 value = [17, 19] class = Yes 16->18 19 AHCNOYR2 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 18->19 24 R_MARITL_4 <= 0.5 entropy = 0.94 samples = 28 value = [10, 18] class = Yes 18->24 20 HYPEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 19->20 23 entropy = 0.0 samples = 5 value = [5, 0] class = No 19->23 21 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 20->21 22 entropy = 0.0 samples = 2 value = [2, 0] class = No 20->22 25 BMI <= 2733.0 entropy = 0.994 samples = 22 value = [10, 12] class = Yes 24->25 36 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 24->36 26 ASISTLV_2.0 <= 0.5 entropy = 0.991 samples = 18 value = [10, 8] class = No 25->26 35 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 25->35 27 ASIRETR_2.0 <= 0.5 entropy = 0.722 samples = 10 value = [8, 2] class = No 26->27 32 BMI <= 2692.0 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 26->32 28 BMI <= 2539.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 27->28 31 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 27->31 29 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 28->29 30 entropy = 0.0 samples = 8 value = [8, 0] class = No 28->30 33 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 32->33 34 entropy = 0.0 samples = 2 value = [2, 0] class = No 32->34 39 YRSWRKPA <= 5.5 entropy = 0.954 samples = 16 value = [6, 10] class = Yes 38->39 50 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 38->50 40 BMI <= 2416.5 entropy = 0.684 samples = 11 value = [2, 9] class = Yes 39->40 45 AMDLONGR_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 39->45 41 R_MARITL_4 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 40->41 44 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 40->44 42 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 41->42 43 entropy = 0.0 samples = 2 value = [2, 0] class = No 41->43 46 AHCNOYR2 <= 1.0 entropy = 1.0 samples = 2 value = [1, 1] class = No 45->46 49 entropy = 0.0 samples = 3 value = [3, 0] class = No 45->49 47 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 46->47 48 entropy = 0.0 samples = 1 value = [1, 0] class = No 46->48 53 HYPEV_2.0 <= 0.5 entropy = 0.683 samples = 265 value = [48, 217] class = Yes 52->53 156 BEDDAYR <= 3.5 entropy = 0.87 samples = 254 value = [74, 180] class = Yes 52->156 54 BMI <= 2793.0 entropy = 0.396 samples = 115 value = [9, 106] class = Yes 53->54 81 YRSWRKPA <= 24.5 entropy = 0.827 samples = 150 value = [39, 111] class = Yes 53->81 55 ASIRETR_2.0 <= 0.5 entropy = 0.305 samples = 110 value = [6, 104] class = Yes 54->55 78 BEDDAYR <= 1.0 entropy = 0.971 samples = 5 value = [3, 2] class = No 54->78 56 R_MARITL_4 <= 0.5 entropy = 0.414 samples = 72 value = [6, 66] class = Yes 55->56 77 entropy = 0.0 samples = 38 value = [0, 38] class = Yes 55->77 57 DOINGLWA_5.0 <= 0.5 entropy = 0.283 samples = 61 value = [3, 58] class = Yes 56->57 70 YRSWRKPA <= 19.5 entropy = 0.845 samples = 11 value = [3, 8] class = Yes 56->70 58 entropy = 0.0 samples = 33 value = [0, 33] class = Yes 57->58 59 HIT1A_2.0 <= 0.5 entropy = 0.491 samples = 28 value = [3, 25] class = Yes 57->59 60 entropy = 0.0 samples = 13 value = [0, 13] class = Yes 59->60 61 BMI <= 2509.5 entropy = 0.722 samples = 15 value = [3, 12] class = Yes 59->61 62 AHEARST1_4.0 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 61->62 69 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 61->69 63 DIBPRE2_2.0 <= 0.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 62->63 68 entropy = 0.0 samples = 1 value = [1, 0] class = No 62->68 64 BMI <= 2470.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 63->64 67 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 63->67 65 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 64->65 66 entropy = 0.0 samples = 2 value = [2, 0] class = No 64->66 71 VIMGLASS_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 70->71 76 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 70->76 72 ASICNHC_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 71->72 75 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 71->75 73 entropy = 0.0 samples = 3 value = [3, 0] class = No 72->73 74 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 72->74 79 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 78->79 80 entropy = 0.0 samples = 3 value = [3, 0] class = No 78->80 82 BMI <= 2212.0 entropy = 0.777 samples = 135 value = [31, 104] class = Yes 81->82 149 BMI <= 2546.0 entropy = 0.997 samples = 15 value = [8, 7] class = No 81->149 83 BEDDAYR <= 1.0 entropy = 0.985 samples = 14 value = [6, 8] class = Yes 82->83 90 AHCNOYR2 <= 7.5 entropy = 0.735 samples = 121 value = [25, 96] class = Yes 82->90 84 ASISTLV_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 83->84 89 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 83->89 85 entropy = 0.0 samples = 5 value = [5, 0] class = No 84->85 86 YRSWRKPA <= 6.0 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 84->86 87 entropy = 0.0 samples = 1 value = [1, 0] class = No 86->87 88 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 86->88 91 PDSICKA_2.0 <= 0.5 entropy = 0.773 samples = 110 value = [25, 85] class = Yes 90->91 148 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 90->148 92 BMI <= 2752.5 entropy = 0.604 samples = 61 value = [9, 52] class = Yes 91->92 115 ASIRETR_4.0 <= 0.5 entropy = 0.911 samples = 49 value = [16, 33] class = Yes 91->115 93 BMI <= 2660.5 entropy = 0.688 samples = 49 value = [9, 40] class = Yes 92->93 114 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 92->114 94 YRSWRKPA <= 8.5 entropy = 0.513 samples = 35 value = [4, 31] class = Yes 93->94 105 FLA1AR_2 <= 0.5 entropy = 0.94 samples = 14 value = [5, 9] class = Yes 93->105 95 entropy = 0.0 samples = 19 value = [0, 19] class = Yes 94->95 96 BMI <= 2533.0 entropy = 0.811 samples = 16 value = [4, 12] class = Yes 94->96 97 BMI <= 2472.5 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 96->97 104 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 96->104 98 YRSWRKPA <= 10.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 97->98 103 entropy = 0.0 samples = 2 value = [2, 0] class = No 97->103 99 BMI <= 2406.0 entropy = 1.0 samples = 4 value = [2, 2] class = No 98->99 102 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 98->102 100 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 99->100 101 entropy = 0.0 samples = 2 value = [2, 0] class = No 99->101 106 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 105->106 107 DIBREL_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 105->107 108 entropy = 0.0 samples = 2 value = [2, 0] class = No 107->108 109 YRSWRKPA <= 1.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 107->109 110 entropy = 0.0 samples = 2 value = [2, 0] class = No 109->110 111 ASIMEDC_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 109->111 112 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 111->112 113 entropy = 0.0 samples = 1 value = [1, 0] class = No 111->113 116 DOINGLWA_5.0 <= 0.5 entropy = 0.932 samples = 46 value = [16, 30] class = Yes 115->116 147 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 115->147 117 CHLEV_2.0 <= 0.5 entropy = 0.977 samples = 34 value = [14, 20] class = Yes 116->117 142 AHCNOYR2 <= 6.5 entropy = 0.65 samples = 12 value = [2, 10] class = Yes 116->142 118 FLUVACYR_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 117->118 123 BEDDAYR <= 9.5 entropy = 0.89 samples = 26 value = [8, 18] class = Yes 117->123 119 AHCNOYR2 <= 2.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 118->119 122 entropy = 0.0 samples = 4 value = [4, 0] class = No 118->122 120 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 119->120 121 entropy = 0.0 samples = 2 value = [2, 0] class = No 119->121 124 R_MARITL_4 <= 0.5 entropy = 0.855 samples = 25 value = [7, 18] class = Yes 123->124 141 entropy = 0.0 samples = 1 value = [1, 0] class = No 123->141 125 YRSWRKPA <= 2.5 entropy = 0.949 samples = 19 value = [7, 12] class = Yes 124->125 140 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 124->140 126 PAINLB_2.0 <= 0.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 125->126 133 DIBPRE2_2.0 <= 0.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 125->133 127 entropy = 0.0 samples = 3 value = [3, 0] class = No 126->127 128 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 126->128 129 HIT1A_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 128->129 132 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 128->132 130 entropy = 0.0 samples = 2 value = [2, 0] class = No 129->130 131 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 129->131 134 entropy = 0.0 samples = 1 value = [1, 0] class = No 133->134 135 YRSWRKPA <= 13.5 entropy = 0.503 samples = 9 value = [1, 8] class = Yes 133->135 136 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 135->136 137 HIT1A_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 135->137 138 entropy = 0.0 samples = 1 value = [1, 0] class = No 137->138 139 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 137->139 143 BMI <= 2766.5 entropy = 0.439 samples = 11 value = [1, 10] class = Yes 142->143 146 entropy = 0.0 samples = 1 value = [1, 0] class = No 142->146 144 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 143->144 145 entropy = 0.0 samples = 1 value = [1, 0] class = No 143->145 150 entropy = 0.0 samples = 5 value = [5, 0] class = No 149->150 151 WRKLYR4_2.0 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 149->151 152 AHCNOYR2 <= 1.0 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 151->152 155 entropy = 0.0 samples = 2 value = [2, 0] class = No 151->155 153 entropy = 0.0 samples = 1 value = [1, 0] class = No 152->153 154 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 152->154 157 FLA1AR_2 <= 0.5 entropy = 0.896 samples = 227 value = [71, 156] class = Yes 156->157 276 BMI <= 2804.0 entropy = 0.503 samples = 27 value = [3, 24] class = Yes 156->276 158 BMI <= 2083.5 entropy = 0.992 samples = 78 value = [35, 43] class = Yes 157->158 199 BMI <= 2110.0 entropy = 0.798 samples = 149 value = [36, 113] class = Yes 157->199 159 entropy = 0.0 samples = 3 value = [3, 0] class = No 158->159 160 BMI <= 2188.5 entropy = 0.984 samples = 75 value = [32, 43] class = Yes 158->160 161 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 160->161 162 BMI <= 2302.5 entropy = 0.995 samples = 70 value = [32, 38] class = Yes 160->162 163 DIBREL_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 162->163 166 YRSWRKPA <= 3.5 entropy = 0.978 samples = 63 value = [26, 37] class = Yes 162->166 164 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 163->164 165 entropy = 0.0 samples = 6 value = [6, 0] class = No 163->165 167 DIBPRE2_2.0 <= 0.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 166->167 170 YRSWRKPA <= 34.0 entropy = 0.931 samples = 52 value = [18, 34] class = Yes 166->170 168 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 167->168 169 entropy = 0.0 samples = 8 value = [8, 0] class = No 167->169 171 BMI <= 2495.0 entropy = 0.867 samples = 45 value = [13, 32] class = Yes 170->171 194 ASIRETR_4.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 170->194 172 CHPAIN6M_4.0 <= 0.5 entropy = 0.391 samples = 13 value = [1, 12] class = Yes 171->172 177 YRSWRKPA <= 6.5 entropy = 0.954 samples = 32 value = [12, 20] class = Yes 171->177 173 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 172->173 174 YRSWRKPA <= 21.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 172->174 175 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 174->175 176 entropy = 0.0 samples = 1 value = [1, 0] class = No 174->176 178 entropy = 0.0 samples = 2 value = [2, 0] class = No 177->178 179 BMI <= 2541.0 entropy = 0.918 samples = 30 value = [10, 20] class = Yes 177->179 180 entropy = 0.0 samples = 2 value = [2, 0] class = No 179->180 181 CHLEV_2.0 <= 0.5 entropy = 0.863 samples = 28 value = [8, 20] class = Yes 179->181 182 DIBREL_2.0 <= 0.5 entropy = 0.567 samples = 15 value = [2, 13] class = Yes 181->182 187 JNTSYMP_2.0 <= 0.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 181->187 183 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 182->183 184 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 182->184 185 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 184->185 186 entropy = 0.0 samples = 2 value = [2, 0] class = No 184->186 188 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 187->188 193 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 187->193 189 entropy = 0.0 samples = 4 value = [4, 0] class = No 188->189 190 HYPEV_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 188->190 191 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 190->191 192 entropy = 0.0 samples = 2 value = [2, 0] class = No 190->192 195 ARTH1_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 194->195 198 entropy = 0.0 samples = 4 value = [4, 0] class = No 194->198 196 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 195->196 197 entropy = 0.0 samples = 1 value = [1, 0] class = No 195->197 200 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 199->200 201 BMI <= 2246.0 entropy = 0.817 samples = 142 value = [36, 106] class = Yes 199->201 202 CHPAIN6M_4.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 201->202 205 YRSWRKPA <= 33.0 entropy = 0.774 samples = 136 value = [31, 105] class = Yes 201->205 203 entropy = 0.0 samples = 5 value = [5, 0] class = No 202->203 204 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 202->204 206 BMI <= 2778.0 entropy = 0.802 samples = 127 value = [31, 96] class = Yes 205->206 275 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 205->275 207 CHPAIN6M_4.0 <= 0.5 entropy = 0.821 samples = 121 value = [31, 90] class = Yes 206->207 274 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 206->274 208 YRSWRKPA <= 1.5 entropy = 0.797 samples = 116 value = [28, 88] class = Yes 207->208 271 ASIRETR_4.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 207->271 209 HYBPLEV_2.0 <= 0.5 entropy = 0.371 samples = 14 value = [1, 13] class = Yes 208->209 214 FLUVACYR_2.0 <= 0.5 entropy = 0.834 samples = 102 value = [27, 75] class = Yes 208->214 210 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 209->210 211 PDSICKA_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 209->211 212 entropy = 0.0 samples = 1 value = [1, 0] class = No 211->212 213 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 211->213 215 BMI <= 2317.5 entropy = 0.918 samples = 57 value = [19, 38] class = Yes 214->215 248 ARTH1_2.0 <= 0.5 entropy = 0.675 samples = 45 value = [8, 37] class = Yes 214->248 216 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 215->216 217 YRSWRKPA <= 2.5 entropy = 0.953 samples = 51 value = [19, 32] class = Yes 215->217 218 entropy = 0.0 samples = 2 value = [2, 0] class = No 217->218 219 BEDDAYR <= 1.5 entropy = 0.931 samples = 49 value = [17, 32] class = Yes 217->219 220 HYPEV_2.0 <= 0.5 entropy = 0.884 samples = 43 value = [13, 30] class = Yes 219->220 243 DOINGLWA_5.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 219->243 221 BMI <= 2692.0 entropy = 0.998 samples = 17 value = [8, 9] class = Yes 220->221 232 BMI <= 2545.5 entropy = 0.706 samples = 26 value = [5, 21] class = Yes 220->232 222 HYBPLEV_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [8, 6] class = No 221->222 231 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 221->231 223 ASIMEDC_4.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 222->223 230 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 222->230 224 SMKSTAT2_3.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 223->224 227 AHCNOYR2 <= 4.0 entropy = 0.592 samples = 7 value = [6, 1] class = No 223->227 225 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 224->225 226 entropy = 0.0 samples = 2 value = [2, 0] class = No 224->226 228 entropy = 0.0 samples = 6 value = [6, 0] class = No 227->228 229 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 227->229 233 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 232->233 234 ASIRETR_4.0 <= 0.5 entropy = 0.896 samples = 16 value = [5, 11] class = Yes 232->234 235 AHCNOYR2 <= 1.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 234->235 238 PAINLB_2.0 <= 0.5 entropy = 0.439 samples = 11 value = [1, 10] class = Yes 234->238 236 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 235->236 237 entropy = 0.0 samples = 4 value = [4, 0] class = No 235->237 239 AHCNOYR2 <= 2.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 238->239 242 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 238->242 240 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 239->240 241 entropy = 0.0 samples = 1 value = [1, 0] class = No 239->241 244 entropy = 0.0 samples = 3 value = [3, 0] class = No 243->244 245 YRSWRKPA <= 20.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 243->245 246 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 245->246 247 entropy = 0.0 samples = 1 value = [1, 0] class = No 245->247 249 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 248->249 250 AHCNOYR2 <= 3.5 entropy = 0.787 samples = 34 value = [8, 26] class = Yes 248->250 251 PAINLB_2.0 <= 0.5 entropy = 0.746 samples = 33 value = [7, 26] class = Yes 250->251 270 entropy = 0.0 samples = 1 value = [1, 0] class = No 250->270 252 BMI <= 2621.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 251->252 259 YRSWRKPA <= 7.5 entropy = 0.619 samples = 26 value = [4, 22] class = Yes 251->259 253 AHCNOYR2 <= 1.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 252->253 258 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 252->258 254 DIBREL_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 253->254 257 entropy = 0.0 samples = 2 value = [2, 0] class = No 253->257 255 entropy = 0.0 samples = 1 value = [1, 0] class = No 254->255 256 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 254->256 260 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 259->260 261 YRSWRKPA <= 19.0 entropy = 0.811 samples = 16 value = [4, 12] class = Yes 259->261 262 BMI <= 2621.5 entropy = 0.918 samples = 12 value = [4, 8] class = Yes 261->262 269 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 261->269 263 YRSWRKPA <= 15.0 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 262->263 268 entropy = 0.0 samples = 2 value = [2, 0] class = No 262->268 264 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 263->264 265 AHCNOYR2 <= 1.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 263->265 266 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 265->266 267 entropy = 0.0 samples = 2 value = [2, 0] class = No 265->267 272 entropy = 0.0 samples = 3 value = [3, 0] class = No 271->272 273 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 271->273 277 FLA1AR_2 <= 0.5 entropy = 0.391 samples = 26 value = [2, 24] class = Yes 276->277 284 entropy = 0.0 samples = 1 value = [1, 0] class = No 276->284 278 entropy = 0.0 samples = 17 value = [0, 17] class = Yes 277->278 279 YRSWRKPA <= 8.0 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 277->279 280 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 279->280 281 BEDDAYR <= 4.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 279->281 282 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 281->282 283 entropy = 0.0 samples = 2 value = [2, 0] class = No 281->283 286 YRSWRKPA <= 19.0 entropy = 0.779 samples = 26 value = [6, 20] class = Yes 285->286 299 BMI <= 2562.5 entropy = 0.999 samples = 70 value = [34, 36] class = Yes 285->299 287 ASICNHC_4.0 <= 0.5 entropy = 0.9 samples = 19 value = [6, 13] class = Yes 286->287 298 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 286->298 288 ASICNHC_2.0 <= 0.5 entropy = 0.619 samples = 13 value = [2, 11] class = Yes 287->288 293 ASIRETR_4.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 287->293 289 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 288->289 290 PDSICKA_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 288->290 291 entropy = 0.0 samples = 2 value = [2, 0] class = No 290->291 292 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 290->292 294 entropy = 0.0 samples = 3 value = [3, 0] class = No 293->294 295 PDSICKA_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 293->295 296 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 295->296 297 entropy = 0.0 samples = 1 value = [1, 0] class = No 295->297 300 BMI <= 2495.0 entropy = 0.907 samples = 31 value = [21, 10] class = No 299->300 317 YRSWRKPA <= 1.5 entropy = 0.918 samples = 39 value = [13, 26] class = Yes 299->317 301 BMI <= 2441.0 entropy = 0.988 samples = 23 value = [13, 10] class = No 300->301 316 entropy = 0.0 samples = 8 value = [8, 0] class = No 300->316 302 BMI <= 2388.5 entropy = 0.934 samples = 20 value = [13, 7] class = No 301->302 315 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 301->315 303 BMI <= 2374.5 entropy = 0.997 samples = 15 value = [8, 7] class = No 302->303 314 entropy = 0.0 samples = 5 value = [5, 0] class = No 302->314 304 ASISTLV_2.0 <= 0.5 entropy = 0.961 samples = 13 value = [8, 5] class = No 303->304 313 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 303->313 305 BMI <= 2248.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 304->305 312 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 304->312 306 entropy = 0.0 samples = 5 value = [5, 0] class = No 305->306 307 BEDDAYR <= 1.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 305->307 308 ARTH1_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 307->308 311 entropy = 0.0 samples = 2 value = [2, 0] class = No 307->311 309 entropy = 0.0 samples = 1 value = [1, 0] class = No 308->309 310 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 308->310 318 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 317->318 319 JNTSYMP_2.0 <= 0.5 entropy = 0.981 samples = 31 value = [13, 18] class = Yes 317->319 320 ASISTLV_2.0 <= 0.5 entropy = 0.503 samples = 9 value = [1, 8] class = Yes 319->320 325 ASIRETR_4.0 <= 0.5 entropy = 0.994 samples = 22 value = [12, 10] class = No 319->325 321 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 320->321 322 AHEARST1_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 320->322 323 entropy = 0.0 samples = 1 value = [1, 0] class = No 322->323 324 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 322->324 326 BMI <= 2766.5 entropy = 0.954 samples = 16 value = [6, 10] class = Yes 325->326 337 entropy = 0.0 samples = 6 value = [6, 0] class = No 325->337 327 BMI <= 2659.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 326->327 336 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 326->336 328 WRKLYR4_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 327->328 333 CHLEV_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 327->333 329 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 328->329 330 HYPEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 328->330 331 entropy = 0.0 samples = 2 value = [2, 0] class = No 330->331 332 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 330->332 334 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 333->334 335 entropy = 0.0 samples = 4 value = [4, 0] class = No 333->335 339 DBHVCLN_2.0 <= 0.5 entropy = 0.956 samples = 220 value = [83, 137] class = Yes 338->339 446 CHLEV_2.0 <= 0.5 entropy = 0.975 samples = 103 value = [61, 42] class = No 338->446 340 HYPEV_2.0 <= 0.5 entropy = 0.994 samples = 130 value = [59, 71] class = Yes 339->340 405 CHPAIN6M_3.0 <= 0.5 entropy = 0.837 samples = 90 value = [24, 66] class = Yes 339->405 341 BMI <= 2148.5 entropy = 0.918 samples = 63 value = [21, 42] class = Yes 340->341 372 PDSICKA_2.0 <= 0.5 entropy = 0.987 samples = 67 value = [38, 29] class = No 340->372 342 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 341->342 343 BMI <= 2742.5 entropy = 0.954 samples = 56 value = [21, 35] class = Yes 341->343 344 PDSICKA_2.0 <= 0.5 entropy = 0.99 samples = 43 value = [19, 24] class = Yes 343->344 367 YRSWRKPA <= 4.0 entropy = 0.619 samples = 13 value = [2, 11] class = Yes 343->367 345 BMI <= 2569.0 entropy = 0.959 samples = 21 value = [13, 8] class = No 344->345 356 BMI <= 2251.5 entropy = 0.845 samples = 22 value = [6, 16] class = Yes 344->356 346 R_MARITL_4 <= 0.5 entropy = 0.997 samples = 15 value = [7, 8] class = Yes 345->346 355 entropy = 0.0 samples = 6 value = [6, 0] class = No 345->355 347 BMI <= 2516.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 346->347 354 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 346->354 348 AHCNOYR2 <= 2.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 347->348 353 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 347->353 349 DIBREL_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 348->349 352 entropy = 0.0 samples = 6 value = [6, 0] class = No 348->352 350 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 349->350 351 entropy = 0.0 samples = 1 value = [1, 0] class = No 349->351 357 entropy = 0.0 samples = 2 value = [2, 0] class = No 356->357 358 BMI <= 2599.5 entropy = 0.722 samples = 20 value = [4, 16] class = Yes 356->358 359 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 358->359 360 HIT1A_2.0 <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 358->360 361 entropy = 0.0 samples = 3 value = [3, 0] class = No 360->361 362 BMI <= 2670.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 360->362 363 ASIMEDC_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 362->363 366 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 362->366 364 entropy = 0.0 samples = 1 value = [1, 0] class = No 363->364 365 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 363->365 368 DIBPRE2_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 367->368 371 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 367->371 369 entropy = 0.0 samples = 2 value = [2, 0] class = No 368->369 370 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 368->370 373 AHCNOYR2 <= 3.5 entropy = 0.99 samples = 34 value = [15, 19] class = Yes 372->373 392 BEDDAYR <= 1.5 entropy = 0.885 samples = 33 value = [23, 10] class = No 372->392 374 JNTSYMP_2.0 <= 0.5 entropy = 0.991 samples = 27 value = [15, 12] class = No 373->374 391 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 373->391 375 BMI <= 2080.0 entropy = 0.592 samples = 7 value = [6, 1] class = No 374->375 378 SMKSTAT2_3.0 <= 0.5 entropy = 0.993 samples = 20 value = [9, 11] class = Yes 374->378 376 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 375->376 377 entropy = 0.0 samples = 6 value = [6, 0] class = No 375->377 379 ASICNHC_4.0 <= 0.5 entropy = 0.998 samples = 17 value = [9, 8] class = No 378->379 390 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 378->390 380 DIBREL_2.0 <= 0.5 entropy = 0.961 samples = 13 value = [5, 8] class = Yes 379->380 389 entropy = 0.0 samples = 4 value = [4, 0] class = No 379->389 381 AHCNOYR2 <= 2.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 380->381 384 FLA1AR_2 <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 380->384 382 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 381->382 383 entropy = 0.0 samples = 1 value = [1, 0] class = No 381->383 385 entropy = 0.0 samples = 3 value = [3, 0] class = No 384->385 386 FLUVACYR_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 384->386 387 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 386->387 388 entropy = 0.0 samples = 1 value = [1, 0] class = No 386->388 393 FLUVACYR_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [6, 8] class = Yes 392->393 400 AHEARST1_4.0 <= 0.5 entropy = 0.485 samples = 19 value = [17, 2] class = No 392->400 394 AHSTATYR_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 393->394 397 BMI <= 2006.0 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 393->397 395 entropy = 0.0 samples = 5 value = [5, 0] class = No 394->395 396 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 394->396 398 entropy = 0.0 samples = 1 value = [1, 0] class = No 397->398 399 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 397->399 401 BEDDAYR <= 228.0 entropy = 0.31 samples = 18 value = [17, 1] class = No 400->401 404 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 400->404 402 entropy = 0.0 samples = 17 value = [17, 0] class = No 401->402 403 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 401->403 406 AMDLONGR_1.0 <= 0.5 entropy = 0.868 samples = 83 value = [24, 59] class = Yes 405->406 445 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 405->445 407 BMI <= 2444.0 entropy = 0.391 samples = 13 value = [1, 12] class = Yes 406->407 412 JNTSYMP_2.0 <= 0.5 entropy = 0.913 samples = 70 value = [23, 47] class = Yes 406->412 408 CHLEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 407->408 411 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 407->411 409 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 408->409 410 entropy = 0.0 samples = 1 value = [1, 0] class = No 408->410 413 BEDDAYR <= 1.5 entropy = 0.758 samples = 32 value = [7, 25] class = Yes 412->413 428 ARTH1_2.0 <= 0.5 entropy = 0.982 samples = 38 value = [16, 22] class = Yes 412->428 414 VIMGLASS_2.0 <= 0.5 entropy = 0.323 samples = 17 value = [1, 16] class = Yes 413->414 419 ASICNHC_4.0 <= 0.5 entropy = 0.971 samples = 15 value = [6, 9] class = Yes 413->419 415 entropy = 0.0 samples = 15 value = [0, 15] class = Yes 414->415 416 PDSICKA_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 414->416 417 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 416->417 418 entropy = 0.0 samples = 1 value = [1, 0] class = No 416->418 420 PAINLB_2.0 <= 0.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 419->420 427 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 419->427 421 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 420->421 426 entropy = 0.0 samples = 3 value = [3, 0] class = No 420->426 422 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 421->422 423 DOINGLWA_5.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 421->423 424 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 423->424 425 entropy = 0.0 samples = 3 value = [3, 0] class = No 423->425 429 ASIRETR_2.0 <= 0.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 428->429 432 YRSWRKPA <= 4.5 entropy = 0.894 samples = 29 value = [9, 20] class = Yes 428->432 430 entropy = 0.0 samples = 7 value = [7, 0] class = No 429->430 431 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 429->431 433 WRKLYR4_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 432->433 438 PDSICKA_2.0 <= 0.5 entropy = 0.629 samples = 19 value = [3, 16] class = Yes 432->438 434 FLUVACYR_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 433->434 437 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 433->437 435 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 434->435 436 entropy = 0.0 samples = 6 value = [6, 0] class = No 434->436 439 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 438->439 440 YRSWRKPA <= 12.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 438->440 441 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 440->441 442 YRSWRKPA <= 31.0 entropy = 0.811 samples = 4 value = [3, 1] class = No 440->442 443 entropy = 0.0 samples = 3 value = [3, 0] class = No 442->443 444 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 442->444 447 BMI <= 2668.5 entropy = 0.998 samples = 57 value = [27, 30] class = Yes 446->447 476 YRSWRKPA <= 14.0 entropy = 0.828 samples = 46 value = [34, 12] class = No 446->476 448 ASIRETR_2.0 <= 0.5 entropy = 0.979 samples = 41 value = [24, 17] class = No 447->448 469 HIT1A_2.0 <= 0.5 entropy = 0.696 samples = 16 value = [3, 13] class = Yes 447->469 449 HYPEV_2.0 <= 0.5 entropy = 0.995 samples = 37 value = [20, 17] class = No 448->449 468 entropy = 0.0 samples = 4 value = [4, 0] class = No 448->468 450 YRSWRKPA <= 27.5 entropy = 0.959 samples = 21 value = [8, 13] class = Yes 449->450 459 AHCNOYR2 <= 2.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 449->459 451 YRSWRKPA <= 17.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 450->451 458 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 450->458 452 DIBPRE2_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 451->452 457 entropy = 0.0 samples = 5 value = [5, 0] class = No 451->457 453 entropy = 0.0 samples = 2 value = [2, 0] class = No 452->453 454 AHSTATYR_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 452->454 455 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 454->455 456 entropy = 0.0 samples = 1 value = [1, 0] class = No 454->456 460 BMI <= 2562.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 459->460 467 entropy = 0.0 samples = 5 value = [5, 0] class = No 459->467 461 YRSWRKPA <= 26.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 460->461 466 entropy = 0.0 samples = 3 value = [3, 0] class = No 460->466 462 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 461->462 463 BMI <= 2107.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 461->463 464 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 463->464 465 entropy = 0.0 samples = 4 value = [4, 0] class = No 463->465 470 AMDLONGR_3.0 <= 0.5 entropy = 0.391 samples = 13 value = [1, 12] class = Yes 469->470 473 BEDDAYR <= 7.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 469->473 471 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 470->471 472 entropy = 0.0 samples = 1 value = [1, 0] class = No 470->472 474 entropy = 0.0 samples = 2 value = [2, 0] class = No 473->474 475 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 473->475 477 ASIRETR_2.0 <= 0.5 entropy = 0.985 samples = 21 value = [12, 9] class = No 476->477 488 HYPEV_2.0 <= 0.5 entropy = 0.529 samples = 25 value = [22, 3] class = No 476->488 478 BMI <= 2279.0 entropy = 0.918 samples = 18 value = [12, 6] class = No 477->478 487 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 477->487 479 entropy = 0.0 samples = 4 value = [4, 0] class = No 478->479 480 BMI <= 2642.0 entropy = 0.985 samples = 14 value = [8, 6] class = No 478->480 481 AHCNOYR2 <= 1.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 480->481 486 entropy = 0.0 samples = 4 value = [4, 0] class = No 480->486 482 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 481->482 483 ARTH1_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 481->483 484 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 483->484 485 entropy = 0.0 samples = 4 value = [4, 0] class = No 483->485 489 YRSWRKPA <= 29.0 entropy = 0.845 samples = 11 value = [8, 3] class = No 488->489 494 entropy = 0.0 samples = 14 value = [14, 0] class = No 488->494 490 VIMGLASS_2.0 <= 0.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 489->490 493 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 489->493 491 entropy = 0.0 samples = 8 value = [8, 0] class = No 490->491 492 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 490->492 496 AHCNOYR2 <= 7.5 entropy = 0.426 samples = 667 value = [58, 609] class = Yes 495->496 649 BMI <= 3533.5 entropy = 0.748 samples = 1489 value = [318, 1171] class = Yes 495->649 497 BMI <= 2914.0 entropy = 0.453 samples = 610 value = [58, 552] class = Yes 496->497 648 entropy = 0.0 samples = 57 value = [0, 57] class = Yes 496->648 498 FLA1AR_2 <= 0.5 entropy = 0.731 samples = 44 value = [9, 35] class = Yes 497->498 513 BEDDAYR <= 3.5 entropy = 0.425 samples = 566 value = [49, 517] class = Yes 497->513 499 entropy = 0.0 samples = 16 value = [0, 16] class = Yes 498->499 500 YRSWRKPA <= 13.5 entropy = 0.906 samples = 28 value = [9, 19] class = Yes 498->500 501 YRSWRKPA <= 4.5 entropy = 0.722 samples = 20 value = [4, 16] class = Yes 500->501 508 FLUVACYR_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 500->508 502 HIT1A_2.0 <= 0.5 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 501->502 507 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 501->507 503 ASISTLV_4.0 <= 0.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 502->503 506 entropy = 0.0 samples = 2 value = [2, 0] class = No 502->506 504 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 503->504 505 entropy = 0.0 samples = 2 value = [2, 0] class = No 503->505 509 entropy = 0.0 samples = 4 value = [4, 0] class = No 508->509 510 DOINGLWA_5.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 508->510 511 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 510->511 512 entropy = 0.0 samples = 1 value = [1, 0] class = No 510->512 514 WRKLYR4_2.0 <= 0.5 entropy = 0.459 samples = 475 value = [46, 429] class = Yes 513->514 637 HIT1A_2.0 <= 0.5 entropy = 0.209 samples = 91 value = [3, 88] class = Yes 513->637 515 AHCNOYR2 <= 5.5 entropy = 0.392 samples = 350 value = [27, 323] class = Yes 514->515 590 CHLEV_2.0 <= 0.5 entropy = 0.615 samples = 125 value = [19, 106] class = Yes 514->590 516 SMKSTAT2_3.0 <= 0.5 entropy = 0.423 samples = 314 value = [27, 287] class = Yes 515->516 589 entropy = 0.0 samples = 36 value = [0, 36] class = Yes 515->589 517 BMI <= 3885.0 entropy = 0.345 samples = 233 value = [15, 218] class = Yes 516->517 562 DBHVCLN_2.0 <= 0.5 entropy = 0.605 samples = 81 value = [12, 69] class = Yes 516->562 518 BMI <= 3839.5 entropy = 0.397 samples = 191 value = [15, 176] class = Yes 517->518 561 entropy = 0.0 samples = 42 value = [0, 42] class = Yes 517->561 519 YRSWRKPA <= 4.5 entropy = 0.342 samples = 188 value = [12, 176] class = Yes 518->519 560 entropy = 0.0 samples = 3 value = [3, 0] class = No 518->560 520 ASIMEDC_4.0 <= 0.5 entropy = 0.519 samples = 86 value = [10, 76] class = Yes 519->520 547 JNTSYMP_2.0 <= 0.5 entropy = 0.139 samples = 102 value = [2, 100] class = Yes 519->547 521 ASICNHC_4.0 <= 0.5 entropy = 0.592 samples = 70 value = [10, 60] class = Yes 520->521 546 entropy = 0.0 samples = 16 value = [0, 16] class = Yes 520->546 522 HIT1A_2.0 <= 0.5 entropy = 0.474 samples = 59 value = [6, 53] class = Yes 521->522 539 YRSWRKPA <= 2.5 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 521->539 523 R_MARITL_4 <= 0.5 entropy = 0.592 samples = 42 value = [6, 36] class = Yes 522->523 538 entropy = 0.0 samples = 17 value = [0, 17] class = Yes 522->538 524 BMI <= 3572.5 entropy = 0.722 samples = 30 value = [6, 24] class = Yes 523->524 537 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 523->537 525 BEDDAYR <= 2.5 entropy = 0.529 samples = 25 value = [3, 22] class = Yes 524->525 534 FLA1AR_2 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 524->534 526 DBHVPAN_2.0 <= 0.5 entropy = 0.414 samples = 24 value = [2, 22] class = Yes 525->526 533 entropy = 0.0 samples = 1 value = [1, 0] class = No 525->533 527 entropy = 0.0 samples = 18 value = [0, 18] class = Yes 526->527 528 BMI <= 3082.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 526->528 529 BMI <= 2972.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 528->529 532 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 528->532 530 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 529->530 531 entropy = 0.0 samples = 2 value = [2, 0] class = No 529->531 535 entropy = 0.0 samples = 3 value = [3, 0] class = No 534->535 536 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 534->536 540 AHCNOYR2 <= 2.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 539->540 545 entropy = 0.0 samples = 2 value = [2, 0] class = No 539->545 541 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 540->541 542 CHPAIN6M_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 540->542 543 entropy = 0.0 samples = 2 value = [2, 0] class = No 542->543 544 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 542->544 548 FLA1AR_2 <= 0.5 entropy = 0.281 samples = 41 value = [2, 39] class = Yes 547->548 559 entropy = 0.0 samples = 61 value = [0, 61] class = Yes 547->559 549 entropy = 0.0 samples = 23 value = [0, 23] class = Yes 548->549 550 PAINLB_2.0 <= 0.5 entropy = 0.503 samples = 18 value = [2, 16] class = Yes 548->550 551 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 550->551 552 FLUVACYR_2.0 <= 0.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 550->552 553 YRSWRKPA <= 32.0 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 552->553 558 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 552->558 554 CHPAIN6M_3.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 553->554 557 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 553->557 555 entropy = 0.0 samples = 2 value = [2, 0] class = No 554->555 556 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 554->556 563 PAINLB_2.0 <= 0.5 entropy = 0.722 samples = 60 value = [12, 48] class = Yes 562->563 588 entropy = 0.0 samples = 21 value = [0, 21] class = Yes 562->588 564 BMI <= 4199.0 entropy = 0.297 samples = 19 value = [1, 18] class = Yes 563->564 569 DIBEV1_3.0 <= 0.5 entropy = 0.839 samples = 41 value = [11, 30] class = Yes 563->569 565 entropy = 0.0 samples = 17 value = [0, 17] class = Yes 564->565 566 DIBREL_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 564->566 567 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 566->567 568 entropy = 0.0 samples = 1 value = [1, 0] class = No 566->568 570 YRSWRKPA <= 29.5 entropy = 0.888 samples = 36 value = [11, 25] class = Yes 569->570 587 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 569->587 571 CHPAIN6M_4.0 <= 0.5 entropy = 0.928 samples = 32 value = [11, 21] class = Yes 570->571 586 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 570->586 572 YRSWRKPA <= 4.0 entropy = 0.85 samples = 29 value = [8, 21] class = Yes 571->572 585 entropy = 0.0 samples = 3 value = [3, 0] class = No 571->585 573 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 572->573 574 YRSWRKPA <= 5.5 entropy = 0.932 samples = 23 value = [8, 15] class = Yes 572->574 575 entropy = 0.0 samples = 4 value = [4, 0] class = No 574->575 576 DOINGLWA_5.0 <= 0.5 entropy = 0.742 samples = 19 value = [4, 15] class = Yes 574->576 577 YRSWRKPA <= 12.0 entropy = 0.65 samples = 18 value = [3, 15] class = Yes 576->577 584 entropy = 0.0 samples = 1 value = [1, 0] class = No 576->584 578 DBHVPAN_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 577->578 583 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 577->583 579 BMI <= 3203.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 578->579 582 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 578->582 580 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 579->580 581 entropy = 0.0 samples = 3 value = [3, 0] class = No 579->581 591 BMI <= 3284.5 entropy = 0.313 samples = 71 value = [4, 67] class = Yes 590->591 606 HIT1A_2.0 <= 0.5 entropy = 0.852 samples = 54 value = [15, 39] class = Yes 590->606 592 BEDDAYR <= 2.5 entropy = 0.485 samples = 38 value = [4, 34] class = Yes 591->592 605 entropy = 0.0 samples = 33 value = [0, 33] class = Yes 591->605 593 BMI <= 3274.0 entropy = 0.406 samples = 37 value = [3, 34] class = Yes 592->593 604 entropy = 0.0 samples = 1 value = [1, 0] class = No 592->604 594 YRSWRKPA <= 23.0 entropy = 0.31 samples = 36 value = [2, 34] class = Yes 593->594 603 entropy = 0.0 samples = 1 value = [1, 0] class = No 593->603 595 entropy = 0.0 samples = 23 value = [0, 23] class = Yes 594->595 596 HIT1A_2.0 <= 0.5 entropy = 0.619 samples = 13 value = [2, 11] class = Yes 594->596 597 ASICNHC_4.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 596->597 602 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 596->602 598 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 597->598 599 BMI <= 3184.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 597->599 600 entropy = 0.0 samples = 2 value = [2, 0] class = No 599->600 601 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 599->601 607 AHEARST1_4.0 <= 0.5 entropy = 0.619 samples = 26 value = [4, 22] class = Yes 606->607 620 AMDLONGR_1.0 <= 0.5 entropy = 0.967 samples = 28 value = [11, 17] class = Yes 606->620 608 FLUVACYR_2.0 <= 0.5 entropy = 0.529 samples = 25 value = [3, 22] class = Yes 607->608 619 entropy = 0.0 samples = 1 value = [1, 0] class = No 607->619 609 BEDDAYR <= 1.5 entropy = 0.722 samples = 15 value = [3, 12] class = Yes 608->609 618 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 608->618 610 CHPAIN6M_4.0 <= 0.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 609->610 617 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 609->617 611 YRSWRKPA <= 16.0 entropy = 1.0 samples = 6 value = [3, 3] class = No 610->611 616 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 610->616 612 entropy = 0.0 samples = 2 value = [2, 0] class = No 611->612 613 FLA1AR_2 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 611->613 614 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 613->614 615 entropy = 0.0 samples = 1 value = [1, 0] class = No 613->615 621 entropy = 0.0 samples = 3 value = [3, 0] class = No 620->621 622 PDSICKA_2.0 <= 0.5 entropy = 0.904 samples = 25 value = [8, 17] class = Yes 620->622 623 BMI <= 2972.5 entropy = 0.414 samples = 12 value = [1, 11] class = Yes 622->623 628 AHCNOYR2 <= 1.5 entropy = 0.996 samples = 13 value = [7, 6] class = No 622->628 624 FLUVACYR_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 623->624 627 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 623->627 625 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 624->625 626 entropy = 0.0 samples = 1 value = [1, 0] class = No 624->626 629 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 628->629 630 BEDDAYR <= 0.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 628->630 631 BMI <= 3745.0 entropy = 0.764 samples = 9 value = [7, 2] class = No 630->631 636 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 630->636 632 entropy = 0.0 samples = 5 value = [5, 0] class = No 631->632 633 JNTSYMP_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 631->633 634 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 633->634 635 entropy = 0.0 samples = 2 value = [2, 0] class = No 633->635 638 entropy = 0.0 samples = 60 value = [0, 60] class = Yes 637->638 639 DIBREL_2.0 <= 0.5 entropy = 0.459 samples = 31 value = [3, 28] class = Yes 637->639 640 entropy = 0.0 samples = 15 value = [0, 15] class = Yes 639->640 641 ASIMEDC_4.0 <= 0.5 entropy = 0.696 samples = 16 value = [3, 13] class = Yes 639->641 642 AHCNOYR2 <= 3.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 641->642 647 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 641->647 643 YRSWRKPA <= 24.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 642->643 646 entropy = 0.0 samples = 2 value = [2, 0] class = No 642->646 644 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 643->644 645 entropy = 0.0 samples = 1 value = [1, 0] class = No 643->645 650 DBHVPAN_2.0 <= 0.5 entropy = 0.795 samples = 1108 value = [266, 842] class = Yes 649->650 1137 BMI <= 4162.0 entropy = 0.575 samples = 381 value = [52, 329] class = Yes 649->1137 651 BMI <= 3503.5 entropy = 0.742 samples = 765 value = [161, 604] class = Yes 650->651 980 AHCNOYR2 <= 1.5 entropy = 0.889 samples = 343 value = [105, 238] class = Yes 650->980 652 ASISTLV_2.0 <= 0.5 entropy = 0.75 samples = 750 value = [161, 589] class = Yes 651->652 979 entropy = 0.0 samples = 15 value = [0, 15] class = Yes 651->979 653 CHPAIN6M_4.0 <= 0.5 entropy = 0.791 samples = 547 value = [130, 417] class = Yes 652->653 906 AHCNOYR2 <= 1.5 entropy = 0.617 samples = 203 value = [31, 172] class = Yes 652->906 654 BMI <= 2906.0 entropy = 0.82 samples = 470 value = [120, 350] class = Yes 653->654 883 BMI <= 2996.5 entropy = 0.557 samples = 77 value = [10, 67] class = Yes 653->883 655 YRSWRKPA <= 1.5 entropy = 0.635 samples = 81 value = [13, 68] class = Yes 654->655 680 BMI <= 2913.5 entropy = 0.849 samples = 389 value = [107, 282] class = Yes 654->680 656 DIBPRE2_2.0 <= 0.5 entropy = 0.94 samples = 14 value = [5, 9] class = Yes 655->656 661 YRSWRKPA <= 6.5 entropy = 0.528 samples = 67 value = [8, 59] class = Yes 655->661 657 entropy = 0.0 samples = 3 value = [3, 0] class = No 656->657 658 WRKLYR4_2.0 <= 0.5 entropy = 0.684 samples = 11 value = [2, 9] class = Yes 656->658 659 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 658->659 660 entropy = 0.0 samples = 2 value = [2, 0] class = No 658->660 662 entropy = 0.0 samples = 16 value = [0, 16] class = Yes 661->662 663 YRSWRKPA <= 10.5 entropy = 0.627 samples = 51 value = [8, 43] class = Yes 661->663 664 BEDDAYR <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 663->664 669 WRKLYR4_2.0 <= 0.5 entropy = 0.454 samples = 42 value = [4, 38] class = Yes 663->669 665 JNTSYMP_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 664->665 668 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 664->668 666 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 665->666 667 entropy = 0.0 samples = 4 value = [4, 0] class = No 665->667 670 entropy = 0.0 samples = 22 value = [0, 22] class = Yes 669->670 671 AHCNOYR2 <= 4.5 entropy = 0.722 samples = 20 value = [4, 16] class = Yes 669->671 672 DBHVCLN_2.0 <= 0.5 entropy = 0.523 samples = 17 value = [2, 15] class = Yes 671->672 677 BEDDAYR <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 671->677 673 entropy = 0.0 samples = 14 value = [0, 14] class = Yes 672->673 674 ASIMEDC_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 672->674 675 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 674->675 676 entropy = 0.0 samples = 2 value = [2, 0] class = No 674->676 678 entropy = 0.0 samples = 2 value = [2, 0] class = No 677->678 679 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 677->679 681 entropy = 0.0 samples = 2 value = [2, 0] class = No 680->681 682 YRSWRKPA <= 26.5 entropy = 0.843 samples = 387 value = [105, 282] class = Yes 680->682 683 R_MARITL_4 <= 0.5 entropy = 0.817 samples = 331 value = [84, 247] class = Yes 682->683 850 AHCNOYR2 <= 1.5 entropy = 0.954 samples = 56 value = [21, 35] class = Yes 682->850 684 HYBPLEV_2.0 <= 0.5 entropy = 0.765 samples = 247 value = [55, 192] class = Yes 683->684 805 BMI <= 3337.0 entropy = 0.93 samples = 84 value = [29, 55] class = Yes 683->805 685 AMDLONGR_3.0 <= 0.5 entropy = 0.802 samples = 209 value = [51, 158] class = Yes 684->685 794 BEDDAYR <= 35.0 entropy = 0.485 samples = 38 value = [4, 34] class = Yes 684->794 686 YRSWRKPA <= 11.5 entropy = 0.783 samples = 202 value = [47, 155] class = Yes 685->686 789 DIBREL_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 685->789 687 AHSTATYR_2.0 <= 0.5 entropy = 0.673 samples = 113 value = [20, 93] class = Yes 686->687 736 BMI <= 3238.0 entropy = 0.885 samples = 89 value = [27, 62] class = Yes 686->736 688 JNTSYMP_2.0 <= 0.5 entropy = 0.706 samples = 104 value = [20, 84] class = Yes 687->688 735 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 687->735 689 DBHVCLN_2.0 <= 0.5 entropy = 0.868 samples = 38 value = [11, 27] class = Yes 688->689 710 AHCNOYR2 <= 3.5 entropy = 0.575 samples = 66 value = [9, 57] class = Yes 688->710 690 BMI <= 3005.5 entropy = 0.776 samples = 35 value = [8, 27] class = Yes 689->690 709 entropy = 0.0 samples = 3 value = [3, 0] class = No 689->709 691 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 690->691 692 BMI <= 3219.5 entropy = 0.863 samples = 28 value = [8, 20] class = Yes 690->692 693 CHLEV_2.0 <= 0.5 entropy = 0.989 samples = 16 value = [7, 9] class = Yes 692->693 706 PAINLB_2.0 <= 0.5 entropy = 0.414 samples = 12 value = [1, 11] class = Yes 692->706 694 WRKLYR4_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 693->694 697 PAINLB_2.0 <= 0.5 entropy = 0.845 samples = 11 value = [3, 8] class = Yes 693->697 695 entropy = 0.0 samples = 4 value = [4, 0] class = No 694->695 696 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 694->696 698 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 697->698 699 ARTH1_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 697->699 700 entropy = 0.0 samples = 2 value = [2, 0] class = No 699->700 701 DIBREL_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 699->701 702 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 701->702 703 ASISTLV_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 701->703 704 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 703->704 705 entropy = 0.0 samples = 1 value = [1, 0] class = No 703->705 707 entropy = 0.0 samples = 1 value = [1, 0] class = No 706->707 708 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 706->708 711 PAINLB_2.0 <= 0.5 entropy = 0.665 samples = 52 value = [9, 43] class = Yes 710->711 734 entropy = 0.0 samples = 14 value = [0, 14] class = Yes 710->734 712 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 711->712 713 AMDLONGR_1.0 <= 0.5 entropy = 0.759 samples = 41 value = [9, 32] class = Yes 711->713 714 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 713->714 715 BMI <= 3235.5 entropy = 0.845 samples = 33 value = [9, 24] class = Yes 713->715 716 YRSWRKPA <= 3.5 entropy = 0.977 samples = 17 value = [7, 10] class = Yes 715->716 729 HIT1A_2.0 <= 0.5 entropy = 0.544 samples = 16 value = [2, 14] class = Yes 715->729 717 AHCNOYR2 <= 2.0 entropy = 0.863 samples = 7 value = [5, 2] class = No 716->717 722 YRSWRKPA <= 9.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 716->722 718 entropy = 0.0 samples = 4 value = [4, 0] class = No 717->718 719 BEDDAYR <= 3.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 717->719 720 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 719->720 721 entropy = 0.0 samples = 1 value = [1, 0] class = No 719->721 723 BMI <= 3159.0 entropy = 0.503 samples = 9 value = [1, 8] class = Yes 722->723 728 entropy = 0.0 samples = 1 value = [1, 0] class = No 722->728 724 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 723->724 725 ARTH1_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 723->725 726 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 725->726 727 entropy = 0.0 samples = 1 value = [1, 0] class = No 725->727 730 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 729->730 731 FLA1AR_2 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 729->731 732 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 731->732 733 entropy = 0.0 samples = 2 value = [2, 0] class = No 731->733 737 BMI <= 3153.0 entropy = 0.761 samples = 59 value = [13, 46] class = Yes 736->737 762 BEDDAYR <= 0.5 entropy = 0.997 samples = 30 value = [14, 16] class = Yes 736->762 738 YRSWRKPA <= 18.5 entropy = 0.859 samples = 46 value = [13, 33] class = Yes 737->738 761 entropy = 0.0 samples = 13 value = [0, 13] class = Yes 737->761 739 BMI <= 3090.5 entropy = 0.967 samples = 28 value = [11, 17] class = Yes 738->739 756 WRKLYR4_2.0 <= 0.5 entropy = 0.503 samples = 18 value = [2, 16] class = Yes 738->756 740 PDSICKA_2.0 <= 0.5 entropy = 0.871 samples = 24 value = [7, 17] class = Yes 739->740 755 entropy = 0.0 samples = 4 value = [4, 0] class = No 739->755 741 YRSWRKPA <= 12.5 entropy = 0.949 samples = 19 value = [7, 12] class = Yes 740->741 754 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 740->754 742 SMKSTAT2_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 741->742 745 BEDDAYR <= 0.5 entropy = 0.837 samples = 15 value = [4, 11] class = Yes 741->745 743 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 742->743 744 entropy = 0.0 samples = 3 value = [3, 0] class = No 742->744 746 YRSWRKPA <= 15.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 745->746 753 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 745->753 747 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 746->747 748 AHCNOYR2 <= 3.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 746->748 749 entropy = 0.0 samples = 3 value = [3, 0] class = No 748->749 750 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 748->750 751 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 750->751 752 entropy = 0.0 samples = 1 value = [1, 0] class = No 750->752 757 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 756->757 758 FLA1AR_2 <= 0.5 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 756->758 759 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 758->759 760 entropy = 0.0 samples = 2 value = [2, 0] class = No 758->760 763 PDSICKA_2.0 <= 0.5 entropy = 0.954 samples = 24 value = [9, 15] class = Yes 762->763 786 BMI <= 3481.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 762->786 764 BMI <= 3399.0 entropy = 0.993 samples = 20 value = [9, 11] class = Yes 763->764 785 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 763->785 765 AHSTATYR_2.0 <= 0.5 entropy = 1.0 samples = 18 value = [9, 9] class = No 764->765 784 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 764->784 766 YRSWRKPA <= 13.5 entropy = 0.989 samples = 16 value = [9, 7] class = No 765->766 783 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 765->783 767 entropy = 0.0 samples = 2 value = [2, 0] class = No 766->767 768 ASISTLV_4.0 <= 0.5 entropy = 1.0 samples = 14 value = [7, 7] class = No 766->768 769 PAINLB_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 768->769 776 PAINLB_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 768->776 770 entropy = 0.0 samples = 1 value = [1, 0] class = No 769->770 771 ARTH1_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 769->771 772 BMI <= 3326.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 771->772 775 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 771->775 773 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 772->773 774 entropy = 0.0 samples = 1 value = [1, 0] class = No 772->774 777 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 776->777 778 BMI <= 3310.0 entropy = 0.65 samples = 6 value = [5, 1] class = No 776->778 779 entropy = 0.0 samples = 3 value = [3, 0] class = No 778->779 780 BMI <= 3347.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 778->780 781 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 780->781 782 entropy = 0.0 samples = 2 value = [2, 0] class = No 780->782 787 entropy = 0.0 samples = 5 value = [5, 0] class = No 786->787 788 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 786->788 790 ASIMEDC_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 789->790 793 entropy = 0.0 samples = 3 value = [3, 0] class = No 789->793 791 entropy = 0.0 samples = 1 value = [1, 0] class = No 790->791 792 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 790->792 795 HYPEV_2.0 <= 0.5 entropy = 0.406 samples = 37 value = [3, 34] class = Yes 794->795 804 entropy = 0.0 samples = 1 value = [1, 0] class = No 794->804 796 YRSWRKPA <= 1.5 entropy = 0.206 samples = 31 value = [1, 30] class = Yes 795->796 801 ASIMEDC_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 795->801 797 VIMGLASS_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 796->797 800 entropy = 0.0 samples = 27 value = [0, 27] class = Yes 796->800 798 entropy = 0.0 samples = 1 value = [1, 0] class = No 797->798 799 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 797->799 802 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 801->802 803 entropy = 0.0 samples = 2 value = [2, 0] class = No 801->803 806 BMI <= 3094.5 entropy = 0.874 samples = 68 value = [20, 48] class = Yes 805->806 841 FLUVACYR_2.0 <= 0.5 entropy = 0.989 samples = 16 value = [9, 7] class = No 805->841 807 HYBPLEV_2.0 <= 0.5 entropy = 0.992 samples = 29 value = [13, 16] class = Yes 806->807 824 ASIRETR_4.0 <= 0.5 entropy = 0.679 samples = 39 value = [7, 32] class = Yes 806->824 808 BMI <= 3083.5 entropy = 0.943 samples = 25 value = [9, 16] class = Yes 807->808 823 entropy = 0.0 samples = 4 value = [4, 0] class = No 807->823 809 ARTH1_2.0 <= 0.5 entropy = 0.845 samples = 22 value = [6, 16] class = Yes 808->809 822 entropy = 0.0 samples = 3 value = [3, 0] class = No 808->822 810 FLA1AR_2 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 809->810 815 DBHVCLN_2.0 <= 0.5 entropy = 0.592 samples = 14 value = [2, 12] class = Yes 809->815 811 BEDDAYR <= 1.0 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 810->811 814 entropy = 0.0 samples = 2 value = [2, 0] class = No 810->814 812 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 811->812 813 entropy = 0.0 samples = 2 value = [2, 0] class = No 811->813 816 YRSWRKPA <= 18.5 entropy = 0.391 samples = 13 value = [1, 12] class = Yes 815->816 821 entropy = 0.0 samples = 1 value = [1, 0] class = No 815->821 817 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 816->817 818 HIT1A_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 816->818 819 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 818->819 820 entropy = 0.0 samples = 1 value = [1, 0] class = No 818->820 825 AHCNOYR2 <= 3.5 entropy = 0.84 samples = 26 value = [7, 19] class = Yes 824->825 840 entropy = 0.0 samples = 13 value = [0, 13] class = Yes 824->840 826 BMI <= 3198.0 entropy = 0.592 samples = 21 value = [3, 18] class = Yes 825->826 837 ASICNHC_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 825->837 827 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 826->827 828 CHLEV_2.0 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 826->828 829 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 828->829 830 HYPEV_2.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 828->830 831 entropy = 0.0 samples = 2 value = [2, 0] class = No 830->831 832 DOINGLWA_5.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 830->832 833 ASIRETR_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 832->833 836 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 832->836 834 entropy = 0.0 samples = 1 value = [1, 0] class = No 833->834 835 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 833->835 838 entropy = 0.0 samples = 4 value = [4, 0] class = No 837->838 839 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 837->839 842 DIBREL_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 841->842 847 AHEARST1_4.0 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 841->847 843 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 842->843 844 PDSICKA_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 842->844 845 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 844->845 846 entropy = 0.0 samples = 2 value = [2, 0] class = No 844->846 848 entropy = 0.0 samples = 7 value = [7, 0] class = No 847->848 849 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 847->849 851 ASIMEDC_2.0 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 850->851 854 SMKSTAT2_3.0 <= 0.5 entropy = 0.871 samples = 48 value = [14, 34] class = Yes 850->854 852 entropy = 0.0 samples = 7 value = [7, 0] class = No 851->852 853 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 851->853 855 VIMGLASS_2.0 <= 0.5 entropy = 0.967 samples = 28 value = [11, 17] class = Yes 854->855 874 BMI <= 3496.5 entropy = 0.61 samples = 20 value = [3, 17] class = Yes 854->874 856 DIBEV1_3.0 <= 0.5 entropy = 0.995 samples = 24 value = [11, 13] class = Yes 855->856 873 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 855->873 857 BMI <= 3267.0 entropy = 0.976 samples = 22 value = [9, 13] class = Yes 856->857 872 entropy = 0.0 samples = 2 value = [2, 0] class = No 856->872 858 BEDDAYR <= 1.5 entropy = 0.998 samples = 19 value = [9, 10] class = Yes 857->858 871 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 857->871 859 ARTH1_2.0 <= 0.5 entropy = 0.977 samples = 17 value = [7, 10] class = Yes 858->859 870 entropy = 0.0 samples = 2 value = [2, 0] class = No 858->870 860 BMI <= 2936.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 859->860 863 HIT1A_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 859->863 861 entropy = 0.0 samples = 1 value = [1, 0] class = No 860->861 862 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 860->862 864 entropy = 0.0 samples = 4 value = [4, 0] class = No 863->864 865 FLA1AR_2 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 863->865 866 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 865->866 867 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 865->867 868 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 867->868 869 entropy = 0.0 samples = 2 value = [2, 0] class = No 867->869 875 BMI <= 2981.5 entropy = 0.485 samples = 19 value = [2, 17] class = Yes 874->875 882 entropy = 0.0 samples = 1 value = [1, 0] class = No 874->882 876 AHCNOYR2 <= 3.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 875->876 881 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 875->881 877 DIBREL_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 876->877 880 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 876->880 878 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 877->878 879 entropy = 0.0 samples = 2 value = [2, 0] class = No 877->879 884 entropy = 0.0 samples = 18 value = [0, 18] class = Yes 883->884 885 BMI <= 3069.5 entropy = 0.657 samples = 59 value = [10, 49] class = Yes 883->885 886 YRSWRKPA <= 1.5 entropy = 0.98 samples = 12 value = [5, 7] class = Yes 885->886 893 HIT1A_2.0 <= 0.5 entropy = 0.489 samples = 47 value = [5, 42] class = Yes 885->893 887 entropy = 0.0 samples = 2 value = [2, 0] class = No 886->887 888 YRSWRKPA <= 22.0 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 886->888 889 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 888->889 890 YRSWRKPA <= 30.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 888->890 891 entropy = 0.0 samples = 3 value = [3, 0] class = No 890->891 892 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 890->892 894 YRSWRKPA <= 18.5 entropy = 0.663 samples = 29 value = [5, 24] class = Yes 893->894 905 entropy = 0.0 samples = 18 value = [0, 18] class = Yes 893->905 895 YRSWRKPA <= 6.5 entropy = 0.831 samples = 19 value = [5, 14] class = Yes 894->895 904 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 894->904 896 DBHVCLN_2.0 <= 0.5 entropy = 0.391 samples = 13 value = [1, 12] class = Yes 895->896 899 AMDLONGR_1.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 895->899 897 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 896->897 898 entropy = 0.0 samples = 1 value = [1, 0] class = No 896->898 900 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 899->900 901 R_MARITL_4 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 899->901 902 entropy = 0.0 samples = 4 value = [4, 0] class = No 901->902 903 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 901->903 907 FLUVACYR_2.0 <= 0.5 entropy = 0.858 samples = 39 value = [11, 28] class = Yes 906->907 928 DIBPRE2_2.0 <= 0.5 entropy = 0.535 samples = 164 value = [20, 144] class = Yes 906->928 908 PAINLB_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [8, 6] class = No 907->908 917 BEDDAYR <= 0.5 entropy = 0.529 samples = 25 value = [3, 22] class = Yes 907->917 909 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 908->909 910 BMI <= 3166.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 908->910 911 entropy = 0.0 samples = 5 value = [5, 0] class = No 910->911 912 BMI <= 3351.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 910->912 913 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 912->913 914 SMKSTAT2_3.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 912->914 915 entropy = 0.0 samples = 3 value = [3, 0] class = No 914->915 916 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 914->916 918 JNTSYMP_2.0 <= 0.5 entropy = 0.75 samples = 14 value = [3, 11] class = Yes 917->918 927 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 917->927 919 YRSWRKPA <= 8.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 918->919 922 YRSWRKPA <= 14.5 entropy = 0.469 samples = 10 value = [1, 9] class = Yes 918->922 920 entropy = 0.0 samples = 2 value = [2, 0] class = No 919->920 921 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 919->921 923 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 922->923 924 HYPEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 922->924 925 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 924->925 926 entropy = 0.0 samples = 1 value = [1, 0] class = No 924->926 929 entropy = 0.0 samples = 27 value = [0, 27] class = Yes 928->929 930 YRSWRKPA <= 13.5 entropy = 0.6 samples = 137 value = [20, 117] class = Yes 928->930 931 YRSWRKPA <= 10.5 entropy = 0.709 samples = 93 value = [18, 75] class = Yes 930->931 972 BMI <= 3482.0 entropy = 0.267 samples = 44 value = [2, 42] class = Yes 930->972 932 BMI <= 2919.0 entropy = 0.626 samples = 83 value = [13, 70] class = Yes 931->932 965 FLUVACYR_2.0 <= 0.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 931->965 933 BMI <= 2901.0 entropy = 0.937 samples = 17 value = [6, 11] class = Yes 932->933 944 YRSWRKPA <= 3.5 entropy = 0.488 samples = 66 value = [7, 59] class = Yes 932->944 934 R_MARITL_4 <= 0.5 entropy = 0.75 samples = 14 value = [3, 11] class = Yes 933->934 943 entropy = 0.0 samples = 3 value = [3, 0] class = No 933->943 935 BMI <= 2876.5 entropy = 0.439 samples = 11 value = [1, 10] class = Yes 934->935 940 BEDDAYR <= 1.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 934->940 936 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 935->936 937 JNTSYMP_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 935->937 938 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 937->938 939 entropy = 0.0 samples = 1 value = [1, 0] class = No 937->939 941 entropy = 0.0 samples = 2 value = [2, 0] class = No 940->941 942 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 940->942 945 BEDDAYR <= 25.0 entropy = 0.65 samples = 42 value = [7, 35] class = Yes 944->945 964 entropy = 0.0 samples = 24 value = [0, 24] class = Yes 944->964 946 ASIRETR_2.0 <= 0.5 entropy = 0.552 samples = 39 value = [5, 34] class = Yes 945->946 961 R_MARITL_4 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 945->961 947 YRSWRKPA <= 2.5 entropy = 0.242 samples = 25 value = [1, 24] class = Yes 946->947 952 ASIMEDC_2.0 <= 0.5 entropy = 0.863 samples = 14 value = [4, 10] class = Yes 946->952 948 entropy = 0.0 samples = 19 value = [0, 19] class = Yes 947->948 949 PAINLB_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 947->949 950 entropy = 0.0 samples = 1 value = [1, 0] class = No 949->950 951 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 949->951 953 BEDDAYR <= 2.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 952->953 956 HIT1A_2.0 <= 0.5 entropy = 0.469 samples = 10 value = [1, 9] class = Yes 952->956 954 entropy = 0.0 samples = 3 value = [3, 0] class = No 953->954 955 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 953->955 957 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 956->957 958 SMKSTAT2_3.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 956->958 959 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 958->959 960 entropy = 0.0 samples = 1 value = [1, 0] class = No 958->960 962 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 961->962 963 entropy = 0.0 samples = 2 value = [2, 0] class = No 961->963 966 YRSWRKPA <= 12.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 965->966 969 ASIRETR_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 965->969 967 entropy = 0.0 samples = 4 value = [4, 0] class = No 966->967 968 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 966->968 970 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 969->970 971 entropy = 0.0 samples = 1 value = [1, 0] class = No 969->971 973 BEDDAYR <= 5.5 entropy = 0.159 samples = 43 value = [1, 42] class = Yes 972->973 978 entropy = 0.0 samples = 1 value = [1, 0] class = No 972->978 974 entropy = 0.0 samples = 41 value = [0, 41] class = Yes 973->974 975 PAINLB_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 973->975 976 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 975->976 977 entropy = 0.0 samples = 1 value = [1, 0] class = No 975->977 981 DBHVCLN_2.0 <= 0.5 entropy = 0.999 samples = 52 value = [25, 27] class = Yes 980->981 1004 ASIMEDC_2.0 <= 0.5 entropy = 0.848 samples = 291 value = [80, 211] class = Yes 980->1004 982 PAINLB_2.0 <= 0.5 entropy = 0.918 samples = 27 value = [18, 9] class = No 981->982 995 BMI <= 2891.5 entropy = 0.855 samples = 25 value = [7, 18] class = Yes 981->995 983 entropy = 0.0 samples = 5 value = [5, 0] class = No 982->983 984 ASISTLV_4.0 <= 0.5 entropy = 0.976 samples = 22 value = [13, 9] class = No 982->984 985 BMI <= 2952.0 entropy = 0.98 samples = 12 value = [5, 7] class = Yes 984->985 990 BMI <= 3170.5 entropy = 0.722 samples = 10 value = [8, 2] class = No 984->990 986 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 985->986 987 BMI <= 3108.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 985->987 988 entropy = 0.0 samples = 5 value = [5, 0] class = No 987->988 989 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 987->989 991 entropy = 0.0 samples = 6 value = [6, 0] class = No 990->991 992 BMI <= 3306.0 entropy = 1.0 samples = 4 value = [2, 2] class = No 990->992 993 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 992->993 994 entropy = 0.0 samples = 2 value = [2, 0] class = No 992->994 996 BMI <= 2845.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 995->996 999 HYBPLEV_2.0 <= 0.5 entropy = 0.61 samples = 20 value = [3, 17] class = Yes 995->999 997 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 996->997 998 entropy = 0.0 samples = 4 value = [4, 0] class = No 996->998 1000 YRSWRKPA <= 30.0 entropy = 0.31 samples = 18 value = [1, 17] class = Yes 999->1000 1003 entropy = 0.0 samples = 2 value = [2, 0] class = No 999->1003 1001 entropy = 0.0 samples = 17 value = [0, 17] class = Yes 1000->1001 1002 entropy = 0.0 samples = 1 value = [1, 0] class = No 1000->1002 1005 BMI <= 3519.0 entropy = 0.901 samples = 205 value = [65, 140] class = Yes 1004->1005 1102 HYPEV_2.0 <= 0.5 entropy = 0.668 samples = 86 value = [15, 71] class = Yes 1004->1102 1006 BMI <= 3405.5 entropy = 0.89 samples = 202 value = [62, 140] class = Yes 1005->1006 1101 entropy = 0.0 samples = 3 value = [3, 0] class = No 1005->1101 1007 YRSWRKPA <= 34.5 entropy = 0.92 samples = 182 value = [61, 121] class = Yes 1006->1007 1096 YRSWRKPA <= 0.5 entropy = 0.286 samples = 20 value = [1, 19] class = Yes 1006->1096 1008 BEDDAYR <= 278.5 entropy = 0.895 samples = 167 value = [52, 115] class = Yes 1007->1008 1089 DIBPRE2_2.0 <= 0.5 entropy = 0.971 samples = 15 value = [9, 6] class = No 1007->1089 1009 HIT1A_2.0 <= 0.5 entropy = 0.885 samples = 165 value = [50, 115] class = Yes 1008->1009 1088 entropy = 0.0 samples = 2 value = [2, 0] class = No 1008->1088 1010 BMI <= 3251.5 entropy = 0.788 samples = 89 value = [21, 68] class = Yes 1009->1010 1043 CHPAIN6M_4.0 <= 0.5 entropy = 0.959 samples = 76 value = [29, 47] class = Yes 1009->1043 1011 DIBPRE2_2.0 <= 0.5 entropy = 0.876 samples = 71 value = [21, 50] class = Yes 1010->1011 1042 entropy = 0.0 samples = 18 value = [0, 18] class = Yes 1010->1042 1012 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 1011->1012 1013 DBHVCLN_2.0 <= 0.5 entropy = 0.939 samples = 59 value = [21, 38] class = Yes 1011->1013 1014 AHCNOYR2 <= 4.5 entropy = 0.997 samples = 32 value = [15, 17] class = Yes 1013->1014 1029 BMI <= 2831.5 entropy = 0.764 samples = 27 value = [6, 21] class = Yes 1013->1029 1015 ARTH1_2.0 <= 0.5 entropy = 0.967 samples = 28 value = [11, 17] class = Yes 1014->1015 1028 entropy = 0.0 samples = 4 value = [4, 0] class = No 1014->1028 1016 CHPAIN6M_4.0 <= 0.5 entropy = 0.503 samples = 9 value = [1, 8] class = Yes 1015->1016 1019 PAINLB_2.0 <= 0.5 entropy = 0.998 samples = 19 value = [10, 9] class = No 1015->1019 1017 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 1016->1017 1018 entropy = 0.0 samples = 1 value = [1, 0] class = No 1016->1018 1020 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1019->1020 1021 R_MARITL_4 <= 0.5 entropy = 0.918 samples = 15 value = [10, 5] class = No 1019->1021 1022 AHSTATYR_2.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 1021->1022 1025 BMI <= 3114.0 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1021->1025 1023 entropy = 0.0 samples = 9 value = [9, 0] class = No 1022->1023 1024 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1022->1024 1026 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1025->1026 1027 entropy = 0.0 samples = 1 value = [1, 0] class = No 1025->1027 1030 entropy = 0.0 samples = 2 value = [2, 0] class = No 1029->1030 1031 JNTSYMP_2.0 <= 0.5 entropy = 0.634 samples = 25 value = [4, 21] class = Yes 1029->1031 1032 CHPAIN6M_4.0 <= 0.5 entropy = 0.918 samples = 12 value = [4, 8] class = Yes 1031->1032 1041 entropy = 0.0 samples = 13 value = [0, 13] class = Yes 1031->1041 1033 AHCNOYR2 <= 5.0 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 1032->1033 1040 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1032->1040 1034 ASIMEDC_4.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 1033->1034 1039 entropy = 0.0 samples = 2 value = [2, 0] class = No 1033->1039 1035 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1034->1035 1036 YRSWRKPA <= 22.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1034->1036 1037 entropy = 0.0 samples = 2 value = [2, 0] class = No 1036->1037 1038 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1036->1038 1044 BMI <= 2882.5 entropy = 0.995 samples = 59 value = [27, 32] class = Yes 1043->1044 1079 BMI <= 3383.0 entropy = 0.523 samples = 17 value = [2, 15] class = Yes 1043->1079 1045 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1044->1045 1046 BMI <= 2966.0 entropy = 1.0 samples = 55 value = [27, 28] class = Yes 1044->1046 1047 FLUVACYR_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 1046->1047 1052 BMI <= 3283.5 entropy = 0.989 samples = 48 value = [21, 27] class = Yes 1046->1052 1048 entropy = 0.0 samples = 5 value = [5, 0] class = No 1047->1048 1049 BMI <= 2919.0 entropy = 1.0 samples = 2 value = [1, 1] class = No 1047->1049 1050 entropy = 0.0 samples = 1 value = [1, 0] class = No 1049->1050 1051 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1049->1051 1053 YRSWRKPA <= 14.5 entropy = 0.954 samples = 40 value = [15, 25] class = Yes 1052->1053 1074 WRKLYR4_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 1052->1074 1054 PAINLB_2.0 <= 0.5 entropy = 0.998 samples = 21 value = [11, 10] class = No 1053->1054 1067 ASISTLV_4.0 <= 0.5 entropy = 0.742 samples = 19 value = [4, 15] class = Yes 1053->1067 1055 WRKLYR4_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 1054->1055 1058 JNTSYMP_2.0 <= 0.5 entropy = 0.971 samples = 15 value = [6, 9] class = Yes 1054->1058 1056 entropy = 0.0 samples = 5 value = [5, 0] class = No 1055->1056 1057 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1055->1057 1059 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1058->1059 1060 FLUVACYR_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 1058->1060 1061 AHCNOYR2 <= 4.0 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 1060->1061 1066 entropy = 0.0 samples = 4 value = [4, 0] class = No 1060->1066 1062 WRKLYR4_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1061->1062 1065 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1061->1065 1063 entropy = 0.0 samples = 2 value = [2, 0] class = No 1062->1063 1064 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1062->1064 1068 BMI <= 3191.0 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 1067->1068 1073 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 1067->1073 1069 YRSWRKPA <= 19.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1068->1069 1072 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1068->1072 1070 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1069->1070 1071 entropy = 0.0 samples = 4 value = [4, 0] class = No 1069->1071 1075 HYPEV_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1074->1075 1078 entropy = 0.0 samples = 4 value = [4, 0] class = No 1074->1078 1076 entropy = 0.0 samples = 2 value = [2, 0] class = No 1075->1076 1077 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1075->1077 1080 ASIRETR_4.0 <= 0.5 entropy = 0.337 samples = 16 value = [1, 15] class = Yes 1079->1080 1087 entropy = 0.0 samples = 1 value = [1, 0] class = No 1079->1087 1081 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 1080->1081 1082 DIBREL_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 1080->1082 1083 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1082->1083 1084 YRSWRKPA <= 22.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1082->1084 1085 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1084->1085 1086 entropy = 0.0 samples = 1 value = [1, 0] class = No 1084->1086 1090 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1089->1090 1091 ASIMEDC_4.0 <= 0.5 entropy = 0.811 samples = 12 value = [9, 3] class = No 1089->1091 1092 DIBREL_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 1091->1092 1095 entropy = 0.0 samples = 7 value = [7, 0] class = No 1091->1095 1093 entropy = 0.0 samples = 2 value = [2, 0] class = No 1092->1093 1094 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1092->1094 1097 FLUVACYR_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1096->1097 1100 entropy = 0.0 samples = 18 value = [0, 18] class = Yes 1096->1100 1098 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1097->1098 1099 entropy = 0.0 samples = 1 value = [1, 0] class = No 1097->1099 1103 AMDLONGR_3.0 <= 0.5 entropy = 0.342 samples = 47 value = [3, 44] class = Yes 1102->1103 1114 BMI <= 2924.5 entropy = 0.89 samples = 39 value = [12, 27] class = Yes 1102->1114 1104 BMI <= 3040.0 entropy = 0.258 samples = 46 value = [2, 44] class = Yes 1103->1104 1113 entropy = 0.0 samples = 1 value = [1, 0] class = No 1103->1113 1105 BMI <= 2988.5 entropy = 0.544 samples = 16 value = [2, 14] class = Yes 1104->1105 1112 entropy = 0.0 samples = 30 value = [0, 30] class = Yes 1104->1112 1106 BMI <= 2828.0 entropy = 0.353 samples = 15 value = [1, 14] class = Yes 1105->1106 1111 entropy = 0.0 samples = 1 value = [1, 0] class = No 1105->1111 1107 PDSICKA_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1106->1107 1110 entropy = 0.0 samples = 13 value = [0, 13] class = Yes 1106->1110 1108 entropy = 0.0 samples = 1 value = [1, 0] class = No 1107->1108 1109 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1107->1109 1115 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 1114->1115 1116 YRSWRKPA <= 23.5 entropy = 0.963 samples = 31 value = [12, 19] class = Yes 1114->1116 1117 BMI <= 3482.5 entropy = 0.996 samples = 26 value = [12, 14] class = Yes 1116->1117 1136 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1116->1136 1118 BMI <= 3190.5 entropy = 0.98 samples = 24 value = [10, 14] class = Yes 1117->1118 1135 entropy = 0.0 samples = 2 value = [2, 0] class = No 1117->1135 1119 BMI <= 2984.0 entropy = 0.971 samples = 10 value = [6, 4] class = No 1118->1119 1126 SMKSTAT2_3.0 <= 0.5 entropy = 0.863 samples = 14 value = [4, 10] class = Yes 1118->1126 1120 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 1119->1120 1125 entropy = 0.0 samples = 4 value = [4, 0] class = No 1119->1125 1121 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1120->1121 1122 AMDLONGR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1120->1122 1123 entropy = 0.0 samples = 2 value = [2, 0] class = No 1122->1123 1124 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1122->1124 1127 AHCNOYR2 <= 6.5 entropy = 0.469 samples = 10 value = [1, 9] class = Yes 1126->1127 1132 DOINGLWA_5.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1126->1132 1128 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1127->1128 1129 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1127->1129 1130 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1129->1130 1131 entropy = 0.0 samples = 1 value = [1, 0] class = No 1129->1131 1133 entropy = 0.0 samples = 3 value = [3, 0] class = No 1132->1133 1134 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1132->1134 1138 HIT1A_2.0 <= 0.5 entropy = 0.612 samples = 318 value = [48, 270] class = Yes 1137->1138 1241 AMDLONGR_2.0 <= 0.5 entropy = 0.341 samples = 63 value = [4, 59] class = Yes 1137->1241 1139 YRSWRKPA <= 3.5 entropy = 0.522 samples = 196 value = [23, 173] class = Yes 1138->1139 1198 ASICNHC_4.0 <= 0.5 entropy = 0.732 samples = 122 value = [25, 97] class = Yes 1138->1198 1140 BMI <= 3906.5 entropy = 0.203 samples = 63 value = [2, 61] class = Yes 1139->1140 1149 AHSTATYR_2.0 <= 0.5 entropy = 0.629 samples = 133 value = [21, 112] class = Yes 1139->1149 1141 entropy = 0.0 samples = 49 value = [0, 49] class = Yes 1140->1141 1142 FLUVACYR_2.0 <= 0.5 entropy = 0.592 samples = 14 value = [2, 12] class = Yes 1140->1142 1143 WRKLYR4_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1142->1143 1148 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 1142->1148 1144 BEDDAYR <= 6.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1143->1144 1147 entropy = 0.0 samples = 1 value = [1, 0] class = No 1143->1147 1145 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1144->1145 1146 entropy = 0.0 samples = 1 value = [1, 0] class = No 1144->1146 1150 ASICNHC_4.0 <= 0.5 entropy = 0.693 samples = 113 value = [21, 92] class = Yes 1149->1150 1197 entropy = 0.0 samples = 20 value = [0, 20] class = Yes 1149->1197 1151 BMI <= 4033.5 entropy = 0.84 samples = 67 value = [18, 49] class = Yes 1150->1151 1186 FLUVACYR_2.0 <= 0.5 entropy = 0.348 samples = 46 value = [3, 43] class = Yes 1150->1186 1152 YRSWRKPA <= 26.5 entropy = 0.881 samples = 60 value = [18, 42] class = Yes 1151->1152 1185 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1151->1185 1153 YRSWRKPA <= 22.5 entropy = 0.826 samples = 54 value = [14, 40] class = Yes 1152->1153 1180 DBHVPAN_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1152->1180 1154 BMI <= 3618.5 entropy = 0.871 samples = 48 value = [14, 34] class = Yes 1153->1154 1179 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1153->1179 1155 YRSWRKPA <= 16.5 entropy = 0.469 samples = 10 value = [1, 9] class = Yes 1154->1155 1158 BMI <= 3667.5 entropy = 0.927 samples = 38 value = [13, 25] class = Yes 1154->1158 1156 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 1155->1156 1157 entropy = 0.0 samples = 1 value = [1, 0] class = No 1155->1157 1159 AHEARST1_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1158->1159 1162 JNTSYMP_2.0 <= 0.5 entropy = 0.845 samples = 33 value = [9, 24] class = Yes 1158->1162 1160 entropy = 0.0 samples = 4 value = [4, 0] class = No 1159->1160 1161 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1159->1161 1163 WRKLYR4_2.0 <= 0.5 entropy = 0.629 samples = 19 value = [3, 16] class = Yes 1162->1163 1168 DIBPRE2_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [6, 8] class = Yes 1162->1168 1164 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 1163->1164 1165 DIBPRE2_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 1163->1165 1166 entropy = 0.0 samples = 3 value = [3, 0] class = No 1165->1166 1167 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1165->1167 1169 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1168->1169 1170 ASIMEDC_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 1168->1170 1171 BMI <= 3896.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 1170->1171 1178 entropy = 0.0 samples = 2 value = [2, 0] class = No 1170->1178 1172 AMDLONGR_5.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1171->1172 1175 BMI <= 4014.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1171->1175 1173 entropy = 0.0 samples = 3 value = [3, 0] class = No 1172->1173 1174 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1172->1174 1176 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1175->1176 1177 entropy = 0.0 samples = 1 value = [1, 0] class = No 1175->1177 1181 PDSICKA_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1180->1181 1184 entropy = 0.0 samples = 3 value = [3, 0] class = No 1180->1184 1182 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1181->1182 1183 entropy = 0.0 samples = 1 value = [1, 0] class = No 1181->1183 1187 entropy = 0.0 samples = 29 value = [0, 29] class = Yes 1186->1187 1188 ASIRETR_2.0 <= 0.5 entropy = 0.672 samples = 17 value = [3, 14] class = Yes 1186->1188 1189 AHCNOYR2 <= 1.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 1188->1189 1196 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1188->1196 1190 entropy = 0.0 samples = 2 value = [2, 0] class = No 1189->1190 1191 ASISTLV_4.0 <= 0.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 1189->1191 1192 PDSICKA_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1191->1192 1195 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1191->1195 1193 entropy = 0.0 samples = 1 value = [1, 0] class = No 1192->1193 1194 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1192->1194 1199 CHPAIN6M_4.0 <= 0.5 entropy = 0.508 samples = 71 value = [8, 63] class = Yes 1198->1199 1216 R_MARITL_4 <= 0.5 entropy = 0.918 samples = 51 value = [17, 34] class = Yes 1198->1216 1200 AHSTATYR_2.0 <= 0.5 entropy = 0.619 samples = 52 value = [8, 44] class = Yes 1199->1200 1215 entropy = 0.0 samples = 19 value = [0, 19] class = Yes 1199->1215 1201 YRSWRKPA <= 2.5 entropy = 0.529 samples = 50 value = [6, 44] class = Yes 1200->1201 1214 entropy = 0.0 samples = 2 value = [2, 0] class = No 1200->1214 1202 entropy = 0.0 samples = 16 value = [0, 16] class = Yes 1201->1202 1203 CHLEV_2.0 <= 0.5 entropy = 0.672 samples = 34 value = [6, 28] class = Yes 1201->1203 1204 BMI <= 4081.0 entropy = 0.297 samples = 19 value = [1, 18] class = Yes 1203->1204 1207 ASISTLV_2.0 <= 0.5 entropy = 0.918 samples = 15 value = [5, 10] class = Yes 1203->1207 1205 entropy = 0.0 samples = 18 value = [0, 18] class = Yes 1204->1205 1206 entropy = 0.0 samples = 1 value = [1, 0] class = No 1204->1206 1208 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 1207->1208 1209 DIBREL_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 1207->1209 1210 entropy = 0.0 samples = 4 value = [4, 0] class = No 1209->1210 1211 AHCNOYR2 <= 2.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1209->1211 1212 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1211->1212 1213 entropy = 0.0 samples = 1 value = [1, 0] class = No 1211->1213 1217 HYPEV_2.0 <= 0.5 entropy = 0.764 samples = 36 value = [8, 28] class = Yes 1216->1217 1234 VIMGLASS_2.0 <= 0.5 entropy = 0.971 samples = 15 value = [9, 6] class = No 1216->1234 1218 CHPAIN6M_3.0 <= 0.5 entropy = 0.89 samples = 26 value = [8, 18] class = Yes 1217->1218 1233 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 1217->1233 1219 BMI <= 3715.0 entropy = 0.982 samples = 19 value = [8, 11] class = Yes 1218->1219 1232 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1218->1232 1220 DBHVPAN_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 1219->1220 1225 PAINLB_2.0 <= 0.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 1219->1225 1221 entropy = 0.0 samples = 5 value = [5, 0] class = No 1220->1221 1222 YRSWRKPA <= 16.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1220->1222 1223 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1222->1223 1224 entropy = 0.0 samples = 1 value = [1, 0] class = No 1222->1224 1226 CHLEV_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1225->1226 1231 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1225->1231 1227 PDSICKA_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1226->1227 1230 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1226->1230 1228 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1227->1228 1229 entropy = 0.0 samples = 2 value = [2, 0] class = No 1227->1229 1235 HYPEV_2.0 <= 0.5 entropy = 0.811 samples = 12 value = [9, 3] class = No 1234->1235 1240 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1234->1240 1236 FLUVACYR_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 1235->1236 1239 entropy = 0.0 samples = 7 value = [7, 0] class = No 1235->1239 1237 entropy = 0.0 samples = 2 value = [2, 0] class = No 1236->1237 1238 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1236->1238 1242 AHCNOYR2 <= 7.5 entropy = 0.137 samples = 52 value = [1, 51] class = Yes 1241->1242 1249 CHLEV_2.0 <= 0.5 entropy = 0.845 samples = 11 value = [3, 8] class = Yes 1241->1249 1243 entropy = 0.0 samples = 40 value = [0, 40] class = Yes 1242->1243 1244 YRSWRKPA <= 12.0 entropy = 0.414 samples = 12 value = [1, 11] class = Yes 1242->1244 1245 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 1244->1245 1246 SMKSTAT2_3.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1244->1246 1247 entropy = 0.0 samples = 1 value = [1, 0] class = No 1246->1247 1248 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1246->1248 1250 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1249->1250 1251 AHCNOYR2 <= 2.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 1249->1251 1252 HYPEV_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 1251->1252 1257 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1251->1257 1253 entropy = 0.0 samples = 2 value = [2, 0] class = No 1252->1253 1254 AHCNOYR2 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1252->1254 1255 entropy = 0.0 samples = 1 value = [1, 0] class = No 1254->1255 1256 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1254->1256 1259 DBHVPAN_2.0 <= 0.5 entropy = 0.853 samples = 3355 value = [2422, 933] class = No 1258->1259 2718 DBHVPAN_2.0 <= 0.5 entropy = 0.559 samples = 6187 value = [5380, 807] class = No 1258->2718 1260 BEDDAYR <= 3.5 entropy = 0.927 samples = 1734 value = [1141, 593] class = No 1259->1260 2099 DBHVCLN_2.0 <= 0.5 entropy = 0.741 samples = 1621 value = [1281, 340] class = No 1259->2099 1261 HYPEV_2.0 <= 0.5 entropy = 0.883 samples = 1372 value = [959, 413] class = No 1260->1261 1930 AHCNOYR2 <= 2.5 entropy = 1.0 samples = 362 value = [182, 180] class = No 1260->1930 1262 AHCNOYR2 <= 1.5 entropy = 0.957 samples = 605 value = [376, 229] class = No 1261->1262 1589 AHCNOYR2 <= 0.5 entropy = 0.795 samples = 767 value = [583, 184] class = No 1261->1589 1263 BMI <= 3015.5 entropy = 0.762 samples = 86 value = [67, 19] class = No 1262->1263 1302 ARTH1_2.0 <= 0.5 entropy = 0.974 samples = 519 value = [309, 210] class = No 1262->1302 1264 BMI <= 2618.5 entropy = 0.561 samples = 61 value = [53, 8] class = No 1263->1264 1287 YRSWRKPA <= 2.5 entropy = 0.99 samples = 25 value = [14, 11] class = No 1263->1287 1265 BMI <= 2598.5 entropy = 0.758 samples = 32 value = [25, 7] class = No 1264->1265 1282 ASISTLV_2.0 <= 0.5 entropy = 0.216 samples = 29 value = [28, 1] class = No 1264->1282 1266 CHLEV_2.0 <= 0.5 entropy = 0.709 samples = 31 value = [25, 6] class = No 1265->1266 1281 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1265->1281 1267 BEDDAYR <= 0.5 entropy = 0.353 samples = 15 value = [14, 1] class = No 1266->1267 1272 BMI <= 2364.0 entropy = 0.896 samples = 16 value = [11, 5] class = No 1266->1272 1268 entropy = 0.0 samples = 13 value = [13, 0] class = No 1267->1268 1269 AMDLONGR_1.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1267->1269 1270 entropy = 0.0 samples = 1 value = [1, 0] class = No 1269->1270 1271 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1269->1271 1273 entropy = 0.0 samples = 5 value = [5, 0] class = No 1272->1273 1274 VIMGLASS_2.0 <= 0.5 entropy = 0.994 samples = 11 value = [6, 5] class = No 1272->1274 1275 AMDLONGR_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 1274->1275 1280 entropy = 0.0 samples = 3 value = [3, 0] class = No 1274->1280 1276 BMI <= 2388.0 entropy = 0.811 samples = 4 value = [3, 1] class = No 1275->1276 1279 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1275->1279 1277 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1276->1277 1278 entropy = 0.0 samples = 3 value = [3, 0] class = No 1276->1278 1283 entropy = 0.0 samples = 26 value = [26, 0] class = No 1282->1283 1284 HIT1A_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1282->1284 1285 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1284->1285 1286 entropy = 0.0 samples = 2 value = [2, 0] class = No 1284->1286 1288 ASIMEDC_4.0 <= 0.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 1287->1288 1293 AHCNOYR2 <= 0.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 1287->1293 1289 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1288->1289 1290 YRSWRKPA <= 1.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1288->1290 1291 entropy = 0.0 samples = 2 value = [2, 0] class = No 1290->1291 1292 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1290->1292 1294 entropy = 0.0 samples = 5 value = [5, 0] class = No 1293->1294 1295 YRSWRKPA <= 22.0 entropy = 0.946 samples = 11 value = [7, 4] class = No 1293->1295 1296 HIT1A_2.0 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 1295->1296 1301 entropy = 0.0 samples = 3 value = [3, 0] class = No 1295->1301 1297 BMI <= 4049.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1296->1297 1300 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1296->1300 1298 entropy = 0.0 samples = 4 value = [4, 0] class = No 1297->1298 1299 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1297->1299 1303 BMI <= 2974.0 entropy = 0.994 samples = 297 value = [162, 135] class = No 1302->1303 1478 BMI <= 3647.5 entropy = 0.923 samples = 222 value = [147, 75] class = No 1302->1478 1304 YRSWRKPA <= 28.5 entropy = 0.978 samples = 206 value = [121, 85] class = No 1303->1304 1427 VIMGLASS_2.0 <= 0.5 entropy = 0.993 samples = 91 value = [41, 50] class = Yes 1303->1427 1305 ASIMEDC_2.0 <= 0.5 entropy = 0.995 samples = 166 value = [90, 76] class = No 1304->1305 1406 R_MARITL_4 <= 0.5 entropy = 0.769 samples = 40 value = [31, 9] class = No 1304->1406 1306 BEDDAYR <= 2.5 entropy = 0.981 samples = 136 value = [79, 57] class = No 1305->1306 1391 YRSWRKPA <= 12.5 entropy = 0.948 samples = 30 value = [11, 19] class = Yes 1305->1391 1307 BMI <= 2968.5 entropy = 0.97 samples = 128 value = [77, 51] class = No 1306->1307 1388 YRSWRKPA <= 18.0 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 1306->1388 1308 BMI <= 2935.0 entropy = 0.975 samples = 125 value = [74, 51] class = No 1307->1308 1387 entropy = 0.0 samples = 3 value = [3, 0] class = No 1307->1387 1309 BMI <= 2922.0 entropy = 0.97 samples = 123 value = [74, 49] class = No 1308->1309 1386 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1308->1386 1310 ASIRETR_4.0 <= 0.5 entropy = 0.977 samples = 119 value = [70, 49] class = No 1309->1310 1385 entropy = 0.0 samples = 4 value = [4, 0] class = No 1309->1385 1311 JNTSYMP_2.0 <= 0.5 entropy = 0.928 samples = 70 value = [46, 24] class = No 1310->1311 1350 BMI <= 2194.5 entropy = 1.0 samples = 49 value = [24, 25] class = Yes 1310->1350 1312 CHLEV_2.0 <= 0.5 entropy = 0.984 samples = 54 value = [31, 23] class = No 1311->1312 1345 CHPAIN6M_3.0 <= 0.5 entropy = 0.337 samples = 16 value = [15, 1] class = No 1311->1345 1313 PAINLB_2.0 <= 0.5 entropy = 0.885 samples = 33 value = [23, 10] class = No 1312->1313 1332 BMI <= 2512.5 entropy = 0.959 samples = 21 value = [8, 13] class = Yes 1312->1332 1314 BMI <= 2629.5 entropy = 0.667 samples = 23 value = [19, 4] class = No 1313->1314 1325 YRSWRKPA <= 14.0 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 1313->1325 1315 PDSICKA_2.0 <= 0.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 1314->1315 1324 entropy = 0.0 samples = 10 value = [10, 0] class = No 1314->1324 1316 CHPAIN6M_3.0 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 1315->1316 1323 entropy = 0.0 samples = 5 value = [5, 0] class = No 1315->1323 1317 AHCNOYR2 <= 3.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1316->1317 1322 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1316->1322 1318 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1317->1318 1319 BMI <= 2471.0 entropy = 0.722 samples = 5 value = [4, 1] class = No 1317->1319 1320 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1319->1320 1321 entropy = 0.0 samples = 4 value = [4, 0] class = No 1319->1321 1326 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1325->1326 1327 AHCNOYR2 <= 4.0 entropy = 0.918 samples = 6 value = [4, 2] class = No 1325->1327 1328 entropy = 0.0 samples = 3 value = [3, 0] class = No 1327->1328 1329 YRSWRKPA <= 22.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1327->1329 1330 entropy = 0.0 samples = 1 value = [1, 0] class = No 1329->1330 1331 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1329->1331 1333 DBHVCLN_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 1332->1333 1338 YRSWRKPA <= 19.0 entropy = 0.619 samples = 13 value = [2, 11] class = Yes 1332->1338 1334 entropy = 0.0 samples = 5 value = [5, 0] class = No 1333->1334 1335 PAINLB_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1333->1335 1336 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1335->1336 1337 entropy = 0.0 samples = 1 value = [1, 0] class = No 1335->1337 1339 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 1338->1339 1340 AHCNOYR2 <= 7.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 1338->1340 1341 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1340->1341 1344 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1340->1344 1342 entropy = 0.0 samples = 2 value = [2, 0] class = No 1341->1342 1343 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1341->1343 1346 entropy = 0.0 samples = 12 value = [12, 0] class = No 1345->1346 1347 AHCNOYR2 <= 4.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1345->1347 1348 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1347->1348 1349 entropy = 0.0 samples = 3 value = [3, 0] class = No 1347->1349 1351 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1350->1351 1352 YRSWRKPA <= 4.0 entropy = 0.994 samples = 44 value = [24, 20] class = No 1350->1352 1353 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1352->1353 1354 ASICNHC_4.0 <= 0.5 entropy = 0.971 samples = 40 value = [24, 16] class = No 1352->1354 1355 entropy = 0.0 samples = 3 value = [3, 0] class = No 1354->1355 1356 BMI <= 2257.5 entropy = 0.987 samples = 37 value = [21, 16] class = No 1354->1356 1357 entropy = 0.0 samples = 3 value = [3, 0] class = No 1356->1357 1358 YRSWRKPA <= 5.5 entropy = 0.998 samples = 34 value = [18, 16] class = No 1356->1358 1359 entropy = 0.0 samples = 2 value = [2, 0] class = No 1358->1359 1360 DBHVCLN_2.0 <= 0.5 entropy = 1.0 samples = 32 value = [16, 16] class = No 1358->1360 1361 YRSWRKPA <= 20.5 entropy = 0.918 samples = 15 value = [10, 5] class = No 1360->1361 1372 YRSWRKPA <= 10.0 entropy = 0.937 samples = 17 value = [6, 11] class = Yes 1360->1372 1362 FLUVACYR_2.0 <= 0.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 1361->1362 1371 entropy = 0.0 samples = 5 value = [5, 0] class = No 1361->1371 1363 PDSICKA_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1362->1363 1366 BMI <= 2806.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1362->1366 1364 entropy = 0.0 samples = 4 value = [4, 0] class = No 1363->1364 1365 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1363->1365 1367 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1366->1367 1368 R_MARITL_4 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1366->1368 1369 entropy = 0.0 samples = 1 value = [1, 0] class = No 1368->1369 1370 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1368->1370 1373 entropy = 0.0 samples = 2 value = [2, 0] class = No 1372->1373 1374 BMI <= 2641.0 entropy = 0.837 samples = 15 value = [4, 11] class = Yes 1372->1374 1375 BMI <= 2565.0 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 1374->1375 1384 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1374->1384 1376 AHEARST1_4.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 1375->1376 1383 entropy = 0.0 samples = 2 value = [2, 0] class = No 1375->1383 1377 BMI <= 2330.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 1376->1377 1382 entropy = 0.0 samples = 1 value = [1, 0] class = No 1376->1382 1378 YRSWRKPA <= 25.0 entropy = 1.0 samples = 2 value = [1, 1] class = No 1377->1378 1381 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1377->1381 1379 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1378->1379 1380 entropy = 0.0 samples = 1 value = [1, 0] class = No 1378->1380 1389 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1388->1389 1390 entropy = 0.0 samples = 2 value = [2, 0] class = No 1388->1390 1392 ASIRETR_2.0 <= 0.5 entropy = 1.0 samples = 20 value = [10, 10] class = No 1391->1392 1401 SMKSTAT2_3.0 <= 0.5 entropy = 0.469 samples = 10 value = [1, 9] class = Yes 1391->1401 1393 entropy = 0.0 samples = 5 value = [5, 0] class = No 1392->1393 1394 AHSTATYR_2.0 <= 0.5 entropy = 0.918 samples = 15 value = [5, 10] class = Yes 1392->1394 1395 DIBREL_2.0 <= 0.5 entropy = 0.65 samples = 12 value = [2, 10] class = Yes 1394->1395 1400 entropy = 0.0 samples = 3 value = [3, 0] class = No 1394->1400 1396 FLUVACYR_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1395->1396 1399 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 1395->1399 1397 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1396->1397 1398 entropy = 0.0 samples = 2 value = [2, 0] class = No 1396->1398 1402 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1401->1402 1403 ASISTLV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1401->1403 1404 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1403->1404 1405 entropy = 0.0 samples = 1 value = [1, 0] class = No 1403->1405 1407 YRSWRKPA <= 34.0 entropy = 0.592 samples = 35 value = [30, 5] class = No 1406->1407 1424 DIBPRE2_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1406->1424 1408 entropy = 0.0 samples = 12 value = [12, 0] class = No 1407->1408 1409 CHPAIN6M_4.0 <= 0.5 entropy = 0.755 samples = 23 value = [18, 5] class = No 1407->1409 1410 AHCNOYR2 <= 5.0 entropy = 0.896 samples = 16 value = [11, 5] class = No 1409->1410 1423 entropy = 0.0 samples = 7 value = [7, 0] class = No 1409->1423 1411 HIT1A_2.0 <= 0.5 entropy = 0.65 samples = 12 value = [10, 2] class = No 1410->1411 1420 HIT1A_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1410->1420 1412 CHPAIN6M_3.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1411->1412 1419 entropy = 0.0 samples = 6 value = [6, 0] class = No 1411->1419 1413 DIBREL_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1412->1413 1418 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1412->1418 1414 ASISTLV_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1413->1414 1417 entropy = 0.0 samples = 3 value = [3, 0] class = No 1413->1417 1415 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1414->1415 1416 entropy = 0.0 samples = 1 value = [1, 0] class = No 1414->1416 1421 entropy = 0.0 samples = 1 value = [1, 0] class = No 1420->1421 1422 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1420->1422 1425 entropy = 0.0 samples = 1 value = [1, 0] class = No 1424->1425 1426 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1424->1426 1428 SMKSTAT2_3.0 <= 0.5 entropy = 0.972 samples = 77 value = [31, 46] class = Yes 1427->1428 1471 WRKLYR4_2.0 <= 0.5 entropy = 0.863 samples = 14 value = [10, 4] class = No 1427->1471 1429 HYBPLEV_2.0 <= 0.5 entropy = 0.872 samples = 41 value = [12, 29] class = Yes 1428->1429 1452 DIBREL_2.0 <= 0.5 entropy = 0.998 samples = 36 value = [19, 17] class = No 1428->1452 1430 BMI <= 3058.0 entropy = 0.928 samples = 35 value = [12, 23] class = Yes 1429->1430 1451 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1429->1451 1431 BMI <= 2992.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1430->1431 1434 BMI <= 3642.0 entropy = 0.85 samples = 29 value = [8, 21] class = Yes 1430->1434 1432 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1431->1432 1433 entropy = 0.0 samples = 4 value = [4, 0] class = No 1431->1433 1435 ASICNHC_4.0 <= 0.5 entropy = 0.684 samples = 22 value = [4, 18] class = Yes 1434->1435 1446 PAINLB_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 1434->1446 1436 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 1435->1436 1437 YRSWRKPA <= 30.0 entropy = 0.918 samples = 12 value = [4, 8] class = Yes 1435->1437 1438 PDSICKA_2.0 <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 1437->1438 1445 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1437->1445 1439 YRSWRKPA <= 4.0 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 1438->1439 1444 entropy = 0.0 samples = 3 value = [3, 0] class = No 1438->1444 1440 YRSWRKPA <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1439->1440 1443 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1439->1443 1441 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1440->1441 1442 entropy = 0.0 samples = 1 value = [1, 0] class = No 1440->1442 1447 BMI <= 3690.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1446->1447 1450 entropy = 0.0 samples = 3 value = [3, 0] class = No 1446->1450 1448 entropy = 0.0 samples = 1 value = [1, 0] class = No 1447->1448 1449 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1447->1449 1453 BMI <= 3048.0 entropy = 0.592 samples = 14 value = [12, 2] class = No 1452->1453 1458 YRSWRKPA <= 18.5 entropy = 0.902 samples = 22 value = [7, 15] class = Yes 1452->1458 1454 R_MARITL_4 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1453->1454 1457 entropy = 0.0 samples = 11 value = [11, 0] class = No 1453->1457 1455 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1454->1455 1456 entropy = 0.0 samples = 1 value = [1, 0] class = No 1454->1456 1459 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1458->1459 1460 WRKLYR4_2.0 <= 0.5 entropy = 0.997 samples = 15 value = [7, 8] class = Yes 1458->1460 1461 ASICNHC_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1460->1461 1464 ASICNHC_4.0 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 1460->1464 1462 entropy = 0.0 samples = 4 value = [4, 0] class = No 1461->1462 1463 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1461->1463 1465 CHPAIN6M_4.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1464->1465 1470 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1464->1470 1466 ASISTLV_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1465->1466 1469 entropy = 0.0 samples = 2 value = [2, 0] class = No 1465->1469 1467 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1466->1467 1468 entropy = 0.0 samples = 1 value = [1, 0] class = No 1466->1468 1472 AHCNOYR2 <= 3.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 1471->1472 1477 entropy = 0.0 samples = 7 value = [7, 0] class = No 1471->1477 1473 entropy = 0.0 samples = 2 value = [2, 0] class = No 1472->1473 1474 BEDDAYR <= 1.0 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1472->1474 1475 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1474->1475 1476 entropy = 0.0 samples = 1 value = [1, 0] class = No 1474->1476 1479 BMI <= 1887.0 entropy = 0.9 samples = 212 value = [145, 67] class = No 1478->1479 1586 AHSTATYR_2.0 <= 0.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 1478->1586 1480 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1479->1480 1481 BMI <= 2363.0 entropy = 0.893 samples = 210 value = [145, 65] class = No 1479->1481 1482 YRSWRKPA <= 0.5 entropy = 0.619 samples = 39 value = [33, 6] class = No 1481->1482 1493 PDSICKA_2.0 <= 0.5 entropy = 0.93 samples = 171 value = [112, 59] class = No 1481->1493 1483 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1482->1483 1484 ASIMEDC_2.0 <= 0.5 entropy = 0.414 samples = 36 value = [33, 3] class = No 1482->1484 1485 HYBPLEV_2.0 <= 0.5 entropy = 0.201 samples = 32 value = [31, 1] class = No 1484->1485 1490 SMKSTAT2_3.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1484->1490 1486 entropy = 0.0 samples = 26 value = [26, 0] class = No 1485->1486 1487 DBHVCLN_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 1485->1487 1488 entropy = 0.0 samples = 5 value = [5, 0] class = No 1487->1488 1489 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1487->1489 1491 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1490->1491 1492 entropy = 0.0 samples = 2 value = [2, 0] class = No 1490->1492 1494 DIBREL_2.0 <= 0.5 entropy = 0.974 samples = 101 value = [60, 41] class = No 1493->1494 1549 DOINGLWA_5.0 <= 0.5 entropy = 0.822 samples = 70 value = [52, 18] class = No 1493->1549 1495 BMI <= 2586.5 entropy = 0.993 samples = 42 value = [19, 23] class = Yes 1494->1495 1514 DBHVCLN_2.0 <= 0.5 entropy = 0.887 samples = 59 value = [41, 18] class = No 1494->1514 1496 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1495->1496 1497 BMI <= 2716.0 entropy = 0.998 samples = 36 value = [19, 17] class = No 1495->1497 1498 entropy = 0.0 samples = 8 value = [8, 0] class = No 1497->1498 1499 BMI <= 3022.0 entropy = 0.967 samples = 28 value = [11, 17] class = Yes 1497->1499 1500 DBHVCLN_2.0 <= 0.5 entropy = 0.65 samples = 12 value = [2, 10] class = Yes 1499->1500 1505 YRSWRKPA <= 3.5 entropy = 0.989 samples = 16 value = [9, 7] class = No 1499->1505 1501 CHLEV_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 1500->1501 1504 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1500->1504 1502 entropy = 0.0 samples = 2 value = [2, 0] class = No 1501->1502 1503 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1501->1503 1506 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1505->1506 1507 YRSWRKPA <= 14.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 1505->1507 1508 entropy = 0.0 samples = 5 value = [5, 0] class = No 1507->1508 1509 DBHVCLN_2.0 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 1507->1509 1510 BMI <= 3137.0 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 1509->1510 1513 entropy = 0.0 samples = 2 value = [2, 0] class = No 1509->1513 1511 entropy = 0.0 samples = 2 value = [2, 0] class = No 1510->1511 1512 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1510->1512 1515 YRSWRKPA <= 11.5 entropy = 0.711 samples = 36 value = [29, 7] class = No 1514->1515 1532 ASIMEDC_2.0 <= 0.5 entropy = 0.999 samples = 23 value = [12, 11] class = No 1514->1532 1516 entropy = 0.0 samples = 12 value = [12, 0] class = No 1515->1516 1517 BMI <= 3020.5 entropy = 0.871 samples = 24 value = [17, 7] class = No 1515->1517 1518 R_MARITL_4 <= 0.5 entropy = 0.964 samples = 18 value = [11, 7] class = No 1517->1518 1531 entropy = 0.0 samples = 6 value = [6, 0] class = No 1517->1531 1519 YRSWRKPA <= 13.5 entropy = 0.997 samples = 15 value = [8, 7] class = No 1518->1519 1530 entropy = 0.0 samples = 3 value = [3, 0] class = No 1518->1530 1520 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1519->1520 1521 BMI <= 2851.5 entropy = 0.961 samples = 13 value = [8, 5] class = No 1519->1521 1522 YRSWRKPA <= 26.0 entropy = 0.764 samples = 9 value = [7, 2] class = No 1521->1522 1527 PAINLB_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1521->1527 1523 entropy = 0.0 samples = 5 value = [5, 0] class = No 1522->1523 1524 BMI <= 2692.0 entropy = 1.0 samples = 4 value = [2, 2] class = No 1522->1524 1525 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1524->1525 1526 entropy = 0.0 samples = 2 value = [2, 0] class = No 1524->1526 1528 entropy = 0.0 samples = 1 value = [1, 0] class = No 1527->1528 1529 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1527->1529 1533 BMI <= 2401.0 entropy = 0.982 samples = 19 value = [8, 11] class = Yes 1532->1533 1548 entropy = 0.0 samples = 4 value = [4, 0] class = No 1532->1548 1534 entropy = 0.0 samples = 2 value = [2, 0] class = No 1533->1534 1535 AHCNOYR2 <= 3.5 entropy = 0.937 samples = 17 value = [6, 11] class = Yes 1533->1535 1536 BEDDAYR <= 1.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 1535->1536 1547 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1535->1547 1537 BMI <= 2503.0 entropy = 0.918 samples = 9 value = [6, 3] class = No 1536->1537 1546 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1536->1546 1538 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1537->1538 1539 YRSWRKPA <= 2.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 1537->1539 1540 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1539->1540 1541 YRSWRKPA <= 27.0 entropy = 0.592 samples = 7 value = [6, 1] class = No 1539->1541 1542 entropy = 0.0 samples = 5 value = [5, 0] class = No 1541->1542 1543 BMI <= 2803.0 entropy = 1.0 samples = 2 value = [1, 1] class = No 1541->1543 1544 entropy = 0.0 samples = 1 value = [1, 0] class = No 1543->1544 1545 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1543->1545 1550 JNTSYMP_2.0 <= 0.5 entropy = 0.963 samples = 31 value = [19, 12] class = No 1549->1550 1569 FLUVACYR_2.0 <= 0.5 entropy = 0.619 samples = 39 value = [33, 6] class = No 1549->1569 1551 ASISTLV_2.0 <= 0.5 entropy = 1.0 samples = 22 value = [11, 11] class = No 1550->1551 1566 BMI <= 3352.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 1550->1566 1552 YRSWRKPA <= 4.5 entropy = 0.954 samples = 16 value = [10, 6] class = No 1551->1552 1561 ASICNHC_4.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 1551->1561 1553 BEDDAYR <= 0.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 1552->1553 1560 entropy = 0.0 samples = 6 value = [6, 0] class = No 1552->1560 1554 BMI <= 3035.0 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 1553->1554 1559 entropy = 0.0 samples = 3 value = [3, 0] class = No 1553->1559 1555 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1554->1555 1556 DBHVCLN_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1554->1556 1557 entropy = 0.0 samples = 1 value = [1, 0] class = No 1556->1557 1558 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1556->1558 1562 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1561->1562 1563 BEDDAYR <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1561->1563 1564 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1563->1564 1565 entropy = 0.0 samples = 1 value = [1, 0] class = No 1563->1565 1567 entropy = 0.0 samples = 8 value = [8, 0] class = No 1566->1567 1568 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1566->1568 1570 HIT1A_2.0 <= 0.5 entropy = 0.811 samples = 24 value = [18, 6] class = No 1569->1570 1585 entropy = 0.0 samples = 15 value = [15, 0] class = No 1569->1585 1571 entropy = 0.0 samples = 5 value = [5, 0] class = No 1570->1571 1572 CHPAIN6M_4.0 <= 0.5 entropy = 0.9 samples = 19 value = [13, 6] class = No 1570->1572 1573 AHSTATYR_2.0 <= 0.5 entropy = 0.954 samples = 16 value = [10, 6] class = No 1572->1573 1584 entropy = 0.0 samples = 3 value = [3, 0] class = No 1572->1584 1574 BMI <= 2882.5 entropy = 0.996 samples = 13 value = [7, 6] class = No 1573->1574 1583 entropy = 0.0 samples = 3 value = [3, 0] class = No 1573->1583 1575 DIBREL_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 1574->1575 1580 ASICNHC_4.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 1574->1580 1576 CHLEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1575->1576 1579 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1575->1579 1577 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1576->1577 1578 entropy = 0.0 samples = 2 value = [2, 0] class = No 1576->1578 1581 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1580->1581 1582 entropy = 0.0 samples = 5 value = [5, 0] class = No 1580->1582 1587 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 1586->1587 1588 entropy = 0.0 samples = 2 value = [2, 0] class = No 1586->1588 1590 BEDDAYR <= 0.5 entropy = 0.35 samples = 76 value = [71, 5] class = No 1589->1590 1609 BMI <= 2534.5 entropy = 0.825 samples = 691 value = [512, 179] class = No 1589->1609 1591 AMDLONGR_2.0 <= 0.5 entropy = 0.127 samples = 57 value = [56, 1] class = No 1590->1591 1598 BMI <= 3202.0 entropy = 0.742 samples = 19 value = [15, 4] class = No 1590->1598 1592 entropy = 0.0 samples = 47 value = [47, 0] class = No 1591->1592 1593 BMI <= 2338.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 1591->1593 1594 DIBREL_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1593->1594 1597 entropy = 0.0 samples = 8 value = [8, 0] class = No 1593->1597 1595 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1594->1595 1596 entropy = 0.0 samples = 1 value = [1, 0] class = No 1594->1596 1599 DBHVCLN_2.0 <= 0.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 1598->1599 1608 entropy = 0.0 samples = 8 value = [8, 0] class = No 1598->1608 1600 entropy = 0.0 samples = 4 value = [4, 0] class = No 1599->1600 1601 BMI <= 2355.0 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 1599->1601 1602 entropy = 0.0 samples = 2 value = [2, 0] class = No 1601->1602 1603 AMDLONGR_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1601->1603 1604 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1603->1604 1605 ARTH1_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1603->1605 1606 entropy = 0.0 samples = 1 value = [1, 0] class = No 1605->1606 1607 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1605->1607 1610 DBHVCLN_2.0 <= 0.5 entropy = 0.722 samples = 300 value = [240, 60] class = No 1609->1610 1727 PDSICKA_2.0 <= 0.5 entropy = 0.887 samples = 391 value = [272, 119] class = No 1609->1727 1611 BMI <= 2472.5 entropy = 0.518 samples = 155 value = [137, 18] class = No 1610->1611 1660 YRSWRKPA <= 28.5 entropy = 0.868 samples = 145 value = [103, 42] class = No 1610->1660 1612 CHLEV_2.0 <= 0.5 entropy = 0.572 samples = 133 value = [115, 18] class = No 1611->1612 1659 entropy = 0.0 samples = 22 value = [22, 0] class = No 1611->1659 1613 VIMGLASS_2.0 <= 0.5 entropy = 0.187 samples = 35 value = [34, 1] class = No 1612->1613 1618 JNTSYMP_2.0 <= 0.5 entropy = 0.666 samples = 98 value = [81, 17] class = No 1612->1618 1614 entropy = 0.0 samples = 31 value = [31, 0] class = No 1613->1614 1615 ASIMEDC_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1613->1615 1616 entropy = 0.0 samples = 3 value = [3, 0] class = No 1615->1616 1617 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1615->1617 1619 WRKLYR4_2.0 <= 0.5 entropy = 0.804 samples = 57 value = [43, 14] class = No 1618->1619 1646 ASICNHC_4.0 <= 0.5 entropy = 0.378 samples = 41 value = [38, 3] class = No 1618->1646 1620 BMI <= 2448.0 entropy = 0.619 samples = 39 value = [33, 6] class = No 1619->1620 1635 DIBREL_2.0 <= 0.5 entropy = 0.991 samples = 18 value = [10, 8] class = No 1619->1635 1621 YRSWRKPA <= 5.5 entropy = 0.503 samples = 36 value = [32, 4] class = No 1620->1621 1632 YRSWRKPA <= 19.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1620->1632 1622 YRSWRKPA <= 1.5 entropy = 0.742 samples = 19 value = [15, 4] class = No 1621->1622 1631 entropy = 0.0 samples = 17 value = [17, 0] class = No 1621->1631 1623 entropy = 0.0 samples = 7 value = [7, 0] class = No 1622->1623 1624 SMKSTAT2_3.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 1622->1624 1625 AHCNOYR2 <= 4.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 1624->1625 1630 entropy = 0.0 samples = 3 value = [3, 0] class = No 1624->1630 1626 ASICNHC_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 1625->1626 1629 entropy = 0.0 samples = 3 value = [3, 0] class = No 1625->1629 1627 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1626->1627 1628 entropy = 0.0 samples = 2 value = [2, 0] class = No 1626->1628 1633 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1632->1633 1634 entropy = 0.0 samples = 1 value = [1, 0] class = No 1632->1634 1636 entropy = 0.0 samples = 6 value = [6, 0] class = No 1635->1636 1637 YRSWRKPA <= 0.5 entropy = 0.918 samples = 12 value = [4, 8] class = Yes 1635->1637 1638 entropy = 0.0 samples = 2 value = [2, 0] class = No 1637->1638 1639 BEDDAYR <= 1.0 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 1637->1639 1640 VIMGLASS_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 1639->1640 1645 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1639->1645 1641 BMI <= 2426.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 1640->1641 1644 entropy = 0.0 samples = 1 value = [1, 0] class = No 1640->1644 1642 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1641->1642 1643 entropy = 0.0 samples = 1 value = [1, 0] class = No 1641->1643 1647 DOINGLWA_5.0 <= 0.5 entropy = 0.592 samples = 21 value = [18, 3] class = No 1646->1647 1658 entropy = 0.0 samples = 20 value = [20, 0] class = No 1646->1658 1648 ASIMEDC_4.0 <= 0.5 entropy = 0.722 samples = 15 value = [12, 3] class = No 1647->1648 1657 entropy = 0.0 samples = 6 value = [6, 0] class = No 1647->1657 1649 BEDDAYR <= 1.5 entropy = 0.592 samples = 14 value = [12, 2] class = No 1648->1649 1656 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1648->1656 1650 HYBPLEV_2.0 <= 0.5 entropy = 0.391 samples = 13 value = [12, 1] class = No 1649->1650 1655 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1649->1655 1651 entropy = 0.0 samples = 11 value = [11, 0] class = No 1650->1651 1652 BMI <= 2328.0 entropy = 1.0 samples = 2 value = [1, 1] class = No 1650->1652 1653 entropy = 0.0 samples = 1 value = [1, 0] class = No 1652->1653 1654 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1652->1654 1661 ASICNHC_2.0 <= 0.5 entropy = 0.902 samples = 132 value = [90, 42] class = No 1660->1661 1726 entropy = 0.0 samples = 13 value = [13, 0] class = No 1660->1726 1662 R_MARITL_4 <= 0.5 entropy = 0.861 samples = 116 value = [83, 33] class = No 1661->1662 1717 YRSWRKPA <= 7.5 entropy = 0.989 samples = 16 value = [7, 9] class = Yes 1661->1717 1663 HIT1A_2.0 <= 0.5 entropy = 0.926 samples = 82 value = [54, 28] class = No 1662->1663 1706 BMI <= 2219.5 entropy = 0.602 samples = 34 value = [29, 5] class = No 1662->1706 1664 SMKSTAT2_3.0 <= 0.5 entropy = 0.811 samples = 44 value = [33, 11] class = No 1663->1664 1687 ASIMEDC_2.0 <= 0.5 entropy = 0.992 samples = 38 value = [21, 17] class = No 1663->1687 1665 ASIRETR_2.0 <= 0.5 entropy = 0.567 samples = 30 value = [26, 4] class = No 1664->1665 1674 YRSWRKPA <= 20.5 entropy = 1.0 samples = 14 value = [7, 7] class = No 1664->1674 1666 AMDLONGR_2.0 <= 0.5 entropy = 0.276 samples = 21 value = [20, 1] class = No 1665->1666 1671 ARTH1_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 1665->1671 1667 entropy = 0.0 samples = 19 value = [19, 0] class = No 1666->1667 1668 ASISTLV_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1666->1668 1669 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1668->1669 1670 entropy = 0.0 samples = 1 value = [1, 0] class = No 1668->1670 1672 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1671->1672 1673 entropy = 0.0 samples = 6 value = [6, 0] class = No 1671->1673 1675 BEDDAYR <= 1.5 entropy = 0.98 samples = 12 value = [7, 5] class = No 1674->1675 1686 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1674->1686 1676 AMDLONGR_1.0 <= 0.5 entropy = 0.881 samples = 10 value = [7, 3] class = No 1675->1676 1685 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1675->1685 1677 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1676->1677 1678 YRSWRKPA <= 6.0 entropy = 0.764 samples = 9 value = [7, 2] class = No 1676->1678 1679 DIBPRE2_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1678->1679 1684 entropy = 0.0 samples = 5 value = [5, 0] class = No 1678->1684 1680 entropy = 0.0 samples = 1 value = [1, 0] class = No 1679->1680 1681 PAINLB_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1679->1681 1682 entropy = 0.0 samples = 1 value = [1, 0] class = No 1681->1682 1683 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1681->1683 1688 BMI <= 2427.0 entropy = 0.997 samples = 32 value = [15, 17] class = Yes 1687->1688 1705 entropy = 0.0 samples = 6 value = [6, 0] class = No 1687->1705 1689 VIMGLASS_2.0 <= 0.5 entropy = 0.991 samples = 27 value = [15, 12] class = No 1688->1689 1704 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1688->1704 1690 DIBREL_2.0 <= 0.5 entropy = 0.954 samples = 24 value = [15, 9] class = No 1689->1690 1703 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1689->1703 1691 entropy = 0.0 samples = 7 value = [7, 0] class = No 1690->1691 1692 AHCNOYR2 <= 3.5 entropy = 0.998 samples = 17 value = [8, 9] class = Yes 1690->1692 1693 YRSWRKPA <= 14.0 entropy = 0.985 samples = 14 value = [8, 6] class = No 1692->1693 1702 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1692->1702 1694 BMI <= 2356.0 entropy = 0.65 samples = 6 value = [5, 1] class = No 1693->1694 1697 YRSWRKPA <= 21.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 1693->1697 1695 entropy = 0.0 samples = 5 value = [5, 0] class = No 1694->1695 1696 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1694->1696 1698 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1697->1698 1699 AHSTATYR_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1697->1699 1700 entropy = 0.0 samples = 3 value = [3, 0] class = No 1699->1700 1701 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1699->1701 1707 YRSWRKPA <= 0.5 entropy = 0.896 samples = 16 value = [11, 5] class = No 1706->1707 1716 entropy = 0.0 samples = 18 value = [18, 0] class = No 1706->1716 1708 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1707->1708 1709 AMDLONGR_2.0 <= 0.5 entropy = 0.619 samples = 13 value = [11, 2] class = No 1707->1709 1710 entropy = 0.0 samples = 8 value = [8, 0] class = No 1709->1710 1711 ASIRETR_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 1709->1711 1712 ASIMEDC_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1711->1712 1715 entropy = 0.0 samples = 2 value = [2, 0] class = No 1711->1715 1713 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1712->1713 1714 entropy = 0.0 samples = 1 value = [1, 0] class = No 1712->1714 1718 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 1717->1718 1719 YRSWRKPA <= 14.0 entropy = 0.881 samples = 10 value = [7, 3] class = No 1717->1719 1720 entropy = 0.0 samples = 4 value = [4, 0] class = No 1719->1720 1721 BEDDAYR <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 1719->1721 1722 YRSWRKPA <= 26.0 entropy = 0.811 samples = 4 value = [3, 1] class = No 1721->1722 1725 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1721->1725 1723 entropy = 0.0 samples = 3 value = [3, 0] class = No 1722->1723 1724 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1722->1724 1728 BMI <= 2540.5 entropy = 0.934 samples = 260 value = [169, 91] class = No 1727->1728 1877 BMI <= 4236.0 entropy = 0.749 samples = 131 value = [103, 28] class = No 1727->1877 1729 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1728->1729 1730 YRSWRKPA <= 4.5 entropy = 0.925 samples = 256 value = [169, 87] class = No 1728->1730 1731 BMI <= 2730.5 entropy = 0.739 samples = 67 value = [53, 14] class = No 1730->1731 1764 YRSWRKPA <= 20.5 entropy = 0.962 samples = 189 value = [116, 73] class = No 1730->1764 1732 entropy = 0.0 samples = 15 value = [15, 0] class = No 1731->1732 1733 ARTH1_2.0 <= 0.5 entropy = 0.84 samples = 52 value = [38, 14] class = No 1731->1733 1734 ASIMEDC_2.0 <= 0.5 entropy = 0.985 samples = 21 value = [12, 9] class = No 1733->1734 1751 AHCNOYR2 <= 6.5 entropy = 0.637 samples = 31 value = [26, 5] class = No 1733->1751 1735 DBHVCLN_2.0 <= 0.5 entropy = 0.896 samples = 16 value = [11, 5] class = No 1734->1735 1748 BMI <= 2984.0 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1734->1748 1736 CHLEV_2.0 <= 0.5 entropy = 0.75 samples = 14 value = [11, 3] class = No 1735->1736 1747 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1735->1747 1737 entropy = 0.0 samples = 6 value = [6, 0] class = No 1736->1737 1738 CHPAIN6M_3.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 1736->1738 1739 ASICNHC_4.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 1738->1739 1746 entropy = 0.0 samples = 3 value = [3, 0] class = No 1738->1746 1740 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1739->1740 1741 YRSWRKPA <= 1.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 1739->1741 1742 entropy = 0.0 samples = 1 value = [1, 0] class = No 1741->1742 1743 AHSTATYR_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1741->1743 1744 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1743->1744 1745 entropy = 0.0 samples = 1 value = [1, 0] class = No 1743->1745 1749 entropy = 0.0 samples = 1 value = [1, 0] class = No 1748->1749 1750 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1748->1750 1752 ASIRETR_2.0 <= 0.5 entropy = 0.491 samples = 28 value = [25, 3] class = No 1751->1752 1761 DBHVCLN_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1751->1761 1753 entropy = 0.0 samples = 16 value = [16, 0] class = No 1752->1753 1754 PAINLB_2.0 <= 0.5 entropy = 0.811 samples = 12 value = [9, 3] class = No 1752->1754 1755 entropy = 0.0 samples = 5 value = [5, 0] class = No 1754->1755 1756 YRSWRKPA <= 2.0 entropy = 0.985 samples = 7 value = [4, 3] class = No 1754->1756 1757 ASIMEDC_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1756->1757 1760 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1756->1760 1758 entropy = 0.0 samples = 4 value = [4, 0] class = No 1757->1758 1759 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1757->1759 1762 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1761->1762 1763 entropy = 0.0 samples = 1 value = [1, 0] class = No 1761->1763 1765 CHPAIN6M_3.0 <= 0.5 entropy = 0.996 samples = 114 value = [61, 53] class = No 1764->1765 1840 AHCNOYR2 <= 6.5 entropy = 0.837 samples = 75 value = [55, 20] class = No 1764->1840 1766 HIT1A_2.0 <= 0.5 entropy = 1.0 samples = 97 value = [48, 49] class = Yes 1765->1766 1833 ASIRETR_2.0 <= 0.5 entropy = 0.787 samples = 17 value = [13, 4] class = No 1765->1833 1767 BMI <= 3331.0 entropy = 0.989 samples = 73 value = [32, 41] class = Yes 1766->1767 1820 BMI <= 2652.0 entropy = 0.918 samples = 24 value = [16, 8] class = No 1766->1820 1768 AHEARST1_4.0 <= 0.5 entropy = 1.0 samples = 62 value = [31, 31] class = No 1767->1768 1817 BMI <= 4436.0 entropy = 0.439 samples = 11 value = [1, 10] class = Yes 1767->1817 1769 DBHVCLN_2.0 <= 0.5 entropy = 0.997 samples = 58 value = [31, 27] class = No 1768->1769 1816 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1768->1816 1770 ASICNHC_2.0 <= 0.5 entropy = 0.965 samples = 41 value = [25, 16] class = No 1769->1770 1803 CHLEV_2.0 <= 0.5 entropy = 0.937 samples = 17 value = [6, 11] class = Yes 1769->1803 1771 DIBEV1_3.0 <= 0.5 entropy = 0.987 samples = 37 value = [21, 16] class = No 1770->1771 1802 entropy = 0.0 samples = 4 value = [4, 0] class = No 1770->1802 1772 PAINLB_2.0 <= 0.5 entropy = 0.96 samples = 34 value = [21, 13] class = No 1771->1772 1801 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1771->1801 1773 YRSWRKPA <= 13.0 entropy = 0.985 samples = 14 value = [6, 8] class = Yes 1772->1773 1786 AMDLONGR_2.0 <= 0.5 entropy = 0.811 samples = 20 value = [15, 5] class = No 1772->1786 1774 BMI <= 2837.0 entropy = 0.994 samples = 11 value = [6, 5] class = No 1773->1774 1785 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1773->1785 1775 VIMGLASS_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1774->1775 1780 CHLEV_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 1774->1780 1776 entropy = 0.0 samples = 3 value = [3, 0] class = No 1775->1776 1777 ARTH1_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1775->1777 1778 entropy = 0.0 samples = 1 value = [1, 0] class = No 1777->1778 1779 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1777->1779 1781 ASICNHC_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1780->1781 1784 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1780->1784 1782 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1781->1782 1783 entropy = 0.0 samples = 2 value = [2, 0] class = No 1781->1783 1787 FLUVACYR_2.0 <= 0.5 entropy = 0.742 samples = 19 value = [15, 4] class = No 1786->1787 1800 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1786->1800 1788 ASICNHC_4.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 1787->1788 1799 entropy = 0.0 samples = 7 value = [7, 0] class = No 1787->1799 1789 ASIRETR_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 1788->1789 1794 ASIRETR_4.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 1788->1794 1790 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1789->1790 1793 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1789->1793 1791 entropy = 0.0 samples = 2 value = [2, 0] class = No 1790->1791 1792 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1790->1792 1795 entropy = 0.0 samples = 5 value = [5, 0] class = No 1794->1795 1796 VIMGLASS_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1794->1796 1797 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1796->1797 1798 entropy = 0.0 samples = 1 value = [1, 0] class = No 1796->1798 1804 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1803->1804 1809 AHCNOYR2 <= 6.5 entropy = 0.684 samples = 11 value = [2, 9] class = Yes 1803->1809 1805 entropy = 0.0 samples = 3 value = [3, 0] class = No 1804->1805 1806 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1804->1806 1807 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1806->1807 1808 entropy = 0.0 samples = 1 value = [1, 0] class = No 1806->1808 1810 YRSWRKPA <= 6.5 entropy = 0.469 samples = 10 value = [1, 9] class = Yes 1809->1810 1815 entropy = 0.0 samples = 1 value = [1, 0] class = No 1809->1815 1811 BEDDAYR <= 1.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1810->1811 1814 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 1810->1814 1812 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1811->1812 1813 entropy = 0.0 samples = 1 value = [1, 0] class = No 1811->1813 1818 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 1817->1818 1819 entropy = 0.0 samples = 1 value = [1, 0] class = No 1817->1819 1821 entropy = 0.0 samples = 4 value = [4, 0] class = No 1820->1821 1822 BMI <= 3077.5 entropy = 0.971 samples = 20 value = [12, 8] class = No 1820->1822 1823 DBHVCLN_2.0 <= 0.5 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 1822->1823 1828 YRSWRKPA <= 12.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 1822->1828 1824 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1823->1824 1825 R_MARITL_4 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 1823->1825 1826 entropy = 0.0 samples = 4 value = [4, 0] class = No 1825->1826 1827 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1825->1827 1829 entropy = 0.0 samples = 6 value = [6, 0] class = No 1828->1829 1830 DBHVCLN_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1828->1830 1831 entropy = 0.0 samples = 2 value = [2, 0] class = No 1830->1831 1832 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1830->1832 1834 entropy = 0.0 samples = 7 value = [7, 0] class = No 1833->1834 1835 DOINGLWA_5.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 1833->1835 1836 BMI <= 3803.0 entropy = 0.592 samples = 7 value = [6, 1] class = No 1835->1836 1839 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1835->1839 1837 entropy = 0.0 samples = 6 value = [6, 0] class = No 1836->1837 1838 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1836->1838 1841 CHLEV_2.0 <= 0.5 entropy = 0.75 samples = 70 value = [55, 15] class = No 1840->1841 1876 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1840->1876 1842 BMI <= 3060.5 entropy = 0.929 samples = 29 value = [19, 10] class = No 1841->1842 1859 JNTSYMP_2.0 <= 0.5 entropy = 0.535 samples = 41 value = [36, 5] class = No 1841->1859 1843 ASICNHC_2.0 <= 0.5 entropy = 0.98 samples = 24 value = [14, 10] class = No 1842->1843 1858 entropy = 0.0 samples = 5 value = [5, 0] class = No 1842->1858 1844 BMI <= 2989.0 entropy = 0.946 samples = 22 value = [14, 8] class = No 1843->1844 1857 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1843->1857 1845 DIBEV1_3.0 <= 0.5 entropy = 0.881 samples = 20 value = [14, 6] class = No 1844->1845 1856 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1844->1856 1846 HIT1A_2.0 <= 0.5 entropy = 0.764 samples = 18 value = [14, 4] class = No 1845->1846 1855 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1845->1855 1847 entropy = 0.0 samples = 9 value = [9, 0] class = No 1846->1847 1848 AHCNOYR2 <= 1.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 1846->1848 1849 entropy = 0.0 samples = 3 value = [3, 0] class = No 1848->1849 1850 DIBPRE2_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 1848->1850 1851 entropy = 0.0 samples = 1 value = [1, 0] class = No 1850->1851 1852 BMI <= 2912.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1850->1852 1853 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1852->1853 1854 entropy = 0.0 samples = 1 value = [1, 0] class = No 1852->1854 1860 AHCNOYR2 <= 1.5 entropy = 0.663 samples = 29 value = [24, 5] class = No 1859->1860 1875 entropy = 0.0 samples = 12 value = [12, 0] class = No 1859->1875 1861 entropy = 0.0 samples = 7 value = [7, 0] class = No 1860->1861 1862 HYBPLEV_2.0 <= 0.5 entropy = 0.773 samples = 22 value = [17, 5] class = No 1860->1862 1863 SMKSTAT2_3.0 <= 0.5 entropy = 0.702 samples = 21 value = [17, 4] class = No 1862->1863 1874 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1862->1874 1864 CHPAIN6M_3.0 <= 0.5 entropy = 0.863 samples = 14 value = [10, 4] class = No 1863->1864 1873 entropy = 0.0 samples = 7 value = [7, 0] class = No 1863->1873 1865 ASIRETR_2.0 <= 0.5 entropy = 0.779 samples = 13 value = [10, 3] class = No 1864->1865 1872 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1864->1872 1866 entropy = 0.0 samples = 7 value = [7, 0] class = No 1865->1866 1867 HIT1A_2.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 1865->1867 1868 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1867->1868 1869 BMI <= 3128.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 1867->1869 1870 entropy = 0.0 samples = 3 value = [3, 0] class = No 1869->1870 1871 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1869->1871 1878 BMI <= 2957.0 entropy = 0.712 samples = 128 value = [103, 25] class = No 1877->1878 1929 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1877->1929 1879 YRSWRKPA <= 1.5 entropy = 0.592 samples = 84 value = [72, 12] class = No 1878->1879 1906 FLUVACYR_2.0 <= 0.5 entropy = 0.876 samples = 44 value = [31, 13] class = No 1878->1906 1880 entropy = 0.0 samples = 19 value = [19, 0] class = No 1879->1880 1881 AHSTATYR_2.0 <= 0.5 entropy = 0.69 samples = 65 value = [53, 12] class = No 1879->1881 1882 ASIMEDC_2.0 <= 0.5 entropy = 0.604 samples = 61 value = [52, 9] class = No 1881->1882 1903 DIBPRE2_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1881->1903 1883 BMI <= 2566.0 entropy = 0.731 samples = 44 value = [35, 9] class = No 1882->1883 1902 entropy = 0.0 samples = 17 value = [17, 0] class = No 1882->1902 1884 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1883->1884 1885 YRSWRKPA <= 32.5 entropy = 0.65 samples = 42 value = [35, 7] class = No 1883->1885 1886 FLUVACYR_2.0 <= 0.5 entropy = 0.552 samples = 39 value = [34, 5] class = No 1885->1886 1899 HIT1A_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 1885->1899 1887 entropy = 0.0 samples = 17 value = [17, 0] class = No 1886->1887 1888 BMI <= 2871.5 entropy = 0.773 samples = 22 value = [17, 5] class = No 1886->1888 1889 AMDLONGR_2.0 <= 0.5 entropy = 0.918 samples = 15 value = [10, 5] class = No 1888->1889 1898 entropy = 0.0 samples = 7 value = [7, 0] class = No 1888->1898 1890 ASISTLV_2.0 <= 0.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 1889->1890 1897 entropy = 0.0 samples = 5 value = [5, 0] class = No 1889->1897 1891 HIT1A_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1890->1891 1894 ASIRETR_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 1890->1894 1892 entropy = 0.0 samples = 4 value = [4, 0] class = No 1891->1892 1893 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1891->1893 1895 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1894->1895 1896 entropy = 0.0 samples = 1 value = [1, 0] class = No 1894->1896 1900 entropy = 0.0 samples = 1 value = [1, 0] class = No 1899->1900 1901 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1899->1901 1904 entropy = 0.0 samples = 1 value = [1, 0] class = No 1903->1904 1905 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1903->1905 1907 DBHVCLN_2.0 <= 0.5 entropy = 0.998 samples = 21 value = [11, 10] class = No 1906->1907 1920 BMI <= 3201.0 entropy = 0.559 samples = 23 value = [20, 3] class = No 1906->1920 1908 JNTSYMP_2.0 <= 0.5 entropy = 0.896 samples = 16 value = [11, 5] class = No 1907->1908 1919 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1907->1919 1909 PAINLB_2.0 <= 0.5 entropy = 0.98 samples = 12 value = [7, 5] class = No 1908->1909 1918 entropy = 0.0 samples = 4 value = [4, 0] class = No 1908->1918 1910 AHCNOYR2 <= 5.0 entropy = 0.881 samples = 10 value = [7, 3] class = No 1909->1910 1917 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1909->1917 1911 entropy = 0.0 samples = 5 value = [5, 0] class = No 1910->1911 1912 ARTH1_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 1910->1912 1913 YRSWRKPA <= 11.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 1912->1913 1916 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1912->1916 1914 entropy = 0.0 samples = 2 value = [2, 0] class = No 1913->1914 1915 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1913->1915 1921 entropy = 0.0 samples = 10 value = [10, 0] class = No 1920->1921 1922 DIBREL_2.0 <= 0.5 entropy = 0.779 samples = 13 value = [10, 3] class = No 1920->1922 1923 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1922->1923 1924 VIMGLASS_2.0 <= 0.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 1922->1924 1925 entropy = 0.0 samples = 8 value = [8, 0] class = No 1924->1925 1926 YRSWRKPA <= 4.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 1924->1926 1927 entropy = 0.0 samples = 2 value = [2, 0] class = No 1926->1927 1928 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1926->1928 1931 FLUVACYR_2.0 <= 0.5 entropy = 0.861 samples = 74 value = [53, 21] class = No 1930->1931 1958 BMI <= 1909.0 entropy = 0.992 samples = 288 value = [129, 159] class = Yes 1930->1958 1932 BMI <= 3585.5 entropy = 0.989 samples = 32 value = [14, 18] class = Yes 1931->1932 1949 AHSTATYR_2.0 <= 0.5 entropy = 0.371 samples = 42 value = [39, 3] class = No 1931->1949 1933 ASIMEDC_2.0 <= 0.5 entropy = 0.918 samples = 27 value = [9, 18] class = Yes 1932->1933 1948 entropy = 0.0 samples = 5 value = [5, 0] class = No 1932->1948 1934 CHLEV_2.0 <= 0.5 entropy = 0.993 samples = 20 value = [9, 11] class = Yes 1933->1934 1947 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1933->1947 1935 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1934->1935 1936 DBHVCLN_2.0 <= 0.5 entropy = 0.989 samples = 16 value = [9, 7] class = No 1934->1936 1937 AHCNOYR2 <= 1.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 1936->1937 1942 ASIMEDC_4.0 <= 0.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 1936->1942 1938 ASIRETR_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 1937->1938 1941 entropy = 0.0 samples = 5 value = [5, 0] class = No 1937->1941 1939 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1938->1939 1940 entropy = 0.0 samples = 1 value = [1, 0] class = No 1938->1940 1943 AHSTATYR_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 1942->1943 1946 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 1942->1946 1944 entropy = 0.0 samples = 3 value = [3, 0] class = No 1943->1944 1945 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1943->1945 1950 entropy = 0.0 samples = 29 value = [29, 0] class = No 1949->1950 1951 PDSICKA_2.0 <= 0.5 entropy = 0.779 samples = 13 value = [10, 3] class = No 1949->1951 1952 entropy = 0.0 samples = 6 value = [6, 0] class = No 1951->1952 1953 BMI <= 2871.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 1951->1953 1954 ASIMEDC_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 1953->1954 1957 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1953->1957 1955 entropy = 0.0 samples = 4 value = [4, 0] class = No 1954->1955 1956 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 1954->1956 1959 entropy = 0.0 samples = 8 value = [8, 0] class = No 1958->1959 1960 BMI <= 2716.5 entropy = 0.987 samples = 280 value = [121, 159] class = Yes 1958->1960 1961 BMI <= 2700.0 entropy = 1.0 samples = 159 value = [81, 78] class = No 1960->1961 2044 DBHVWLY_2.0 <= 0.5 entropy = 0.916 samples = 121 value = [40, 81] class = Yes 1960->2044 1962 YRSWRKPA <= 11.0 entropy = 1.0 samples = 154 value = [76, 78] class = Yes 1961->1962 2043 entropy = 0.0 samples = 5 value = [5, 0] class = No 1961->2043 1963 HIT1A_2.0 <= 0.5 entropy = 0.977 samples = 85 value = [50, 35] class = No 1962->1963 2008 BEDDAYR <= 20.5 entropy = 0.956 samples = 69 value = [26, 43] class = Yes 1962->2008 1964 AHSTATYR_2.0 <= 0.5 entropy = 0.941 samples = 67 value = [43, 24] class = No 1963->1964 1999 PAINLB_2.0 <= 0.5 entropy = 0.964 samples = 18 value = [7, 11] class = Yes 1963->1999 1965 BMI <= 2651.5 entropy = 0.985 samples = 49 value = [28, 21] class = No 1964->1965 1994 BMI <= 2140.5 entropy = 0.65 samples = 18 value = [15, 3] class = No 1964->1994 1966 VIMGLASS_2.0 <= 0.5 entropy = 0.966 samples = 46 value = [28, 18] class = No 1965->1966 1993 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1965->1993 1967 BMI <= 2069.5 entropy = 0.999 samples = 31 value = [16, 15] class = No 1966->1967 1986 ASICNHC_4.0 <= 0.5 entropy = 0.722 samples = 15 value = [12, 3] class = No 1966->1986 1968 entropy = 0.0 samples = 3 value = [3, 0] class = No 1967->1968 1969 BMI <= 2628.5 entropy = 0.996 samples = 28 value = [13, 15] class = Yes 1967->1969 1970 BEDDAYR <= 55.0 entropy = 0.971 samples = 25 value = [10, 15] class = Yes 1969->1970 1985 entropy = 0.0 samples = 3 value = [3, 0] class = No 1969->1985 1971 AHCNOYR2 <= 7.5 entropy = 0.994 samples = 22 value = [10, 12] class = Yes 1970->1971 1984 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1970->1984 1972 HYBPLEV_2.0 <= 0.5 entropy = 0.961 samples = 13 value = [8, 5] class = No 1971->1972 1979 BEDDAYR <= 10.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 1971->1979 1973 BEDDAYR <= 10.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 1972->1973 1978 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1972->1978 1974 BEDDAYR <= 5.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 1973->1974 1977 entropy = 0.0 samples = 5 value = [5, 0] class = No 1973->1977 1975 entropy = 0.0 samples = 3 value = [3, 0] class = No 1974->1975 1976 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1974->1976 1980 JNTSYMP_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 1979->1980 1983 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 1979->1983 1981 entropy = 0.0 samples = 2 value = [2, 0] class = No 1980->1981 1982 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 1980->1982 1987 DBHVCLN_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 1986->1987 1992 entropy = 0.0 samples = 6 value = [6, 0] class = No 1986->1992 1988 entropy = 0.0 samples = 4 value = [4, 0] class = No 1987->1988 1989 PAINLB_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 1987->1989 1990 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1989->1990 1991 entropy = 0.0 samples = 2 value = [2, 0] class = No 1989->1991 1995 ASIRETR_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 1994->1995 1998 entropy = 0.0 samples = 14 value = [14, 0] class = No 1994->1998 1996 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 1995->1996 1997 entropy = 0.0 samples = 1 value = [1, 0] class = No 1995->1997 2000 R_MARITL_4 <= 0.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 1999->2000 2007 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 1999->2007 2001 BEDDAYR <= 9.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 2000->2001 2006 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2000->2006 2002 HYBPLEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2001->2002 2005 entropy = 0.0 samples = 6 value = [6, 0] class = No 2001->2005 2003 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2002->2003 2004 entropy = 0.0 samples = 1 value = [1, 0] class = No 2002->2004 2009 PDSICKA_2.0 <= 0.5 entropy = 0.998 samples = 40 value = [19, 21] class = Yes 2008->2009 2030 AHEARST1_4.0 <= 0.5 entropy = 0.797 samples = 29 value = [7, 22] class = Yes 2008->2030 2010 BMI <= 2652.5 entropy = 0.931 samples = 26 value = [9, 17] class = Yes 2009->2010 2021 ARTH1_2.0 <= 0.5 entropy = 0.863 samples = 14 value = [10, 4] class = No 2009->2021 2011 BEDDAYR <= 16.0 entropy = 0.976 samples = 22 value = [9, 13] class = Yes 2010->2011 2020 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2010->2020 2012 BMI <= 2576.5 entropy = 0.9 samples = 19 value = [6, 13] class = Yes 2011->2012 2019 entropy = 0.0 samples = 3 value = [3, 0] class = No 2011->2019 2013 BMI <= 2332.5 entropy = 0.696 samples = 16 value = [3, 13] class = Yes 2012->2013 2018 entropy = 0.0 samples = 3 value = [3, 0] class = No 2012->2018 2014 ASIMEDC_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2013->2014 2017 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 2013->2017 2015 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2014->2015 2016 entropy = 0.0 samples = 3 value = [3, 0] class = No 2014->2016 2022 AHCNOYR2 <= 3.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 2021->2022 2029 entropy = 0.0 samples = 5 value = [5, 0] class = No 2021->2029 2023 entropy = 0.0 samples = 3 value = [3, 0] class = No 2022->2023 2024 YRSWRKPA <= 28.0 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 2022->2024 2025 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2024->2025 2026 HYBPLEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2024->2026 2027 entropy = 0.0 samples = 2 value = [2, 0] class = No 2026->2027 2028 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2026->2028 2031 ASIRETR_2.0 <= 0.5 entropy = 0.949 samples = 19 value = [7, 12] class = Yes 2030->2031 2042 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 2030->2042 2032 AHCNOYR2 <= 4.5 entropy = 0.996 samples = 13 value = [7, 6] class = No 2031->2032 2041 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2031->2041 2033 entropy = 0.0 samples = 3 value = [3, 0] class = No 2032->2033 2034 YRSWRKPA <= 23.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 2032->2034 2035 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2034->2035 2036 PDSICKA_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 2034->2036 2037 entropy = 0.0 samples = 3 value = [3, 0] class = No 2036->2037 2038 AHSTATYR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2036->2038 2039 entropy = 0.0 samples = 1 value = [1, 0] class = No 2038->2039 2040 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2038->2040 2045 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2044->2045 2046 DOINGLWA_5.0 <= 0.5 entropy = 0.935 samples = 114 value = [40, 74] class = Yes 2044->2046 2047 DBHVCLN_2.0 <= 0.5 entropy = 0.996 samples = 56 value = [26, 30] class = Yes 2046->2047 2078 DIBPRE2_2.0 <= 0.5 entropy = 0.797 samples = 58 value = [14, 44] class = Yes 2046->2078 2048 PDSICKA_2.0 <= 0.5 entropy = 0.989 samples = 41 value = [23, 18] class = No 2047->2048 2073 YRSWRKPA <= 6.0 entropy = 0.722 samples = 15 value = [3, 12] class = Yes 2047->2073 2049 ARTH1_2.0 <= 0.5 entropy = 0.959 samples = 21 value = [8, 13] class = Yes 2048->2049 2062 JNTSYMP_2.0 <= 0.5 entropy = 0.811 samples = 20 value = [15, 5] class = No 2048->2062 2050 FLUVACYR_2.0 <= 0.5 entropy = 0.98 samples = 12 value = [7, 5] class = No 2049->2050 2057 ASIMEDC_4.0 <= 0.5 entropy = 0.503 samples = 9 value = [1, 8] class = Yes 2049->2057 2051 YRSWRKPA <= 3.0 entropy = 0.592 samples = 7 value = [6, 1] class = No 2050->2051 2054 CHPAIN6M_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2050->2054 2052 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2051->2052 2053 entropy = 0.0 samples = 6 value = [6, 0] class = No 2051->2053 2055 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2054->2055 2056 entropy = 0.0 samples = 1 value = [1, 0] class = No 2054->2056 2058 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2057->2058 2059 ASIRETR_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2057->2059 2060 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2059->2060 2061 entropy = 0.0 samples = 1 value = [1, 0] class = No 2059->2061 2063 ASIMEDC_4.0 <= 0.5 entropy = 0.94 samples = 14 value = [9, 5] class = No 2062->2063 2072 entropy = 0.0 samples = 6 value = [6, 0] class = No 2062->2072 2064 BMI <= 2905.0 entropy = 0.811 samples = 12 value = [9, 3] class = No 2063->2064 2071 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2063->2071 2065 AMDLONGR_1.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2064->2065 2068 BEDDAYR <= 35.0 entropy = 0.503 samples = 9 value = [8, 1] class = No 2064->2068 2066 entropy = 0.0 samples = 1 value = [1, 0] class = No 2065->2066 2067 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2065->2067 2069 entropy = 0.0 samples = 8 value = [8, 0] class = No 2068->2069 2070 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2068->2070 2074 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 2073->2074 2075 AHCNOYR2 <= 4.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 2073->2075 2076 entropy = 0.0 samples = 3 value = [3, 0] class = No 2075->2076 2077 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2075->2077 2079 entropy = 0.0 samples = 11 value = [0, 11] class = Yes 2078->2079 2080 ASIMEDC_4.0 <= 0.5 entropy = 0.879 samples = 47 value = [14, 33] class = Yes 2078->2080 2081 DIBREL_2.0 <= 0.5 entropy = 0.663 samples = 29 value = [5, 24] class = Yes 2080->2081 2090 AHCNOYR2 <= 6.5 entropy = 1.0 samples = 18 value = [9, 9] class = No 2080->2090 2082 YRSWRKPA <= 1.5 entropy = 0.94 samples = 14 value = [5, 9] class = Yes 2081->2082 2089 entropy = 0.0 samples = 15 value = [0, 15] class = Yes 2081->2089 2083 entropy = 0.0 samples = 2 value = [2, 0] class = No 2082->2083 2084 JNTSYMP_2.0 <= 0.5 entropy = 0.811 samples = 12 value = [3, 9] class = Yes 2082->2084 2085 BEDDAYR <= 14.0 entropy = 0.469 samples = 10 value = [1, 9] class = Yes 2084->2085 2088 entropy = 0.0 samples = 2 value = [2, 0] class = No 2084->2088 2086 entropy = 0.0 samples = 1 value = [1, 0] class = No 2085->2086 2087 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 2085->2087 2091 YRSWRKPA <= 18.5 entropy = 0.94 samples = 14 value = [5, 9] class = Yes 2090->2091 2098 entropy = 0.0 samples = 4 value = [4, 0] class = No 2090->2098 2092 VIMGLASS_2.0 <= 0.5 entropy = 0.684 samples = 11 value = [2, 9] class = Yes 2091->2092 2097 entropy = 0.0 samples = 3 value = [3, 0] class = No 2091->2097 2093 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 2092->2093 2094 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2092->2094 2095 entropy = 0.0 samples = 2 value = [2, 0] class = No 2094->2095 2096 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2094->2096 2100 AHCNOYR2 <= 1.5 entropy = 0.906 samples = 373 value = [253, 120] class = No 2099->2100 2283 AHCNOYR2 <= 0.5 entropy = 0.672 samples = 1248 value = [1028, 220] class = No 2099->2283 2101 BEDDAYR <= 1.5 entropy = 0.627 samples = 70 value = [59, 11] class = No 2100->2101 2124 FLUVACYR_2.0 <= 0.5 entropy = 0.942 samples = 303 value = [194, 109] class = No 2100->2124 2102 PAINLB_2.0 <= 0.5 entropy = 0.434 samples = 56 value = [51, 5] class = No 2101->2102 2117 ASICNHC_2.0 <= 0.5 entropy = 0.985 samples = 14 value = [8, 6] class = No 2101->2117 2103 ARTH1_2.0 <= 0.5 entropy = 0.702 samples = 21 value = [17, 4] class = No 2102->2103 2112 YRSWRKPA <= 3.0 entropy = 0.187 samples = 35 value = [34, 1] class = No 2102->2112 2104 entropy = 0.0 samples = 8 value = [8, 0] class = No 2103->2104 2105 BMI <= 2429.0 entropy = 0.89 samples = 13 value = [9, 4] class = No 2103->2105 2106 entropy = 0.0 samples = 4 value = [4, 0] class = No 2105->2106 2107 BMI <= 2764.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 2105->2107 2108 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2107->2108 2109 YRSWRKPA <= 13.0 entropy = 0.65 samples = 6 value = [5, 1] class = No 2107->2109 2110 entropy = 0.0 samples = 5 value = [5, 0] class = No 2109->2110 2111 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2109->2111 2113 ARTH1_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 2112->2113 2116 entropy = 0.0 samples = 28 value = [28, 0] class = No 2112->2116 2114 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2113->2114 2115 entropy = 0.0 samples = 6 value = [6, 0] class = No 2113->2115 2118 YRSWRKPA <= 10.0 entropy = 0.503 samples = 9 value = [8, 1] class = No 2117->2118 2123 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2117->2123 2119 entropy = 0.0 samples = 6 value = [6, 0] class = No 2118->2119 2120 ASIRETR_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2118->2120 2121 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2120->2121 2122 entropy = 0.0 samples = 2 value = [2, 0] class = No 2120->2122 2125 BMI <= 3254.0 entropy = 0.985 samples = 180 value = [103, 77] class = No 2124->2125 2224 YRSWRKPA <= 12.5 entropy = 0.827 samples = 123 value = [91, 32] class = No 2124->2224 2126 CHLEV_2.0 <= 0.5 entropy = 0.954 samples = 144 value = [90, 54] class = No 2125->2126 2201 YRSWRKPA <= 16.5 entropy = 0.944 samples = 36 value = [13, 23] class = Yes 2125->2201 2127 AHSTATYR_2.0 <= 0.5 entropy = 0.997 samples = 66 value = [35, 31] class = No 2126->2127 2162 YRSWRKPA <= 12.5 entropy = 0.875 samples = 78 value = [55, 23] class = No 2126->2162 2128 BMI <= 2239.0 entropy = 0.998 samples = 57 value = [27, 30] class = Yes 2127->2128 2159 BEDDAYR <= 10.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 2127->2159 2129 ASIRETR_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 2128->2129 2134 ASIMEDC_2.0 <= 0.5 entropy = 0.981 samples = 50 value = [21, 29] class = Yes 2128->2134 2130 entropy = 0.0 samples = 5 value = [5, 0] class = No 2129->2130 2131 AHCNOYR2 <= 3.0 entropy = 1.0 samples = 2 value = [1, 1] class = No 2129->2131 2132 entropy = 0.0 samples = 1 value = [1, 0] class = No 2131->2132 2133 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2131->2133 2135 ASISTLV_2.0 <= 0.5 entropy = 1.0 samples = 42 value = [21, 21] class = No 2134->2135 2158 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 2134->2158 2136 ASIRETR_4.0 <= 0.5 entropy = 0.992 samples = 38 value = [21, 17] class = No 2135->2136 2157 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2135->2157 2137 SMKSTAT2_3.0 <= 0.5 entropy = 0.696 samples = 16 value = [13, 3] class = No 2136->2137 2144 BMI <= 3006.5 entropy = 0.946 samples = 22 value = [8, 14] class = Yes 2136->2144 2138 JNTSYMP_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 2137->2138 2143 entropy = 0.0 samples = 8 value = [8, 0] class = No 2137->2143 2139 YRSWRKPA <= 9.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2138->2139 2142 entropy = 0.0 samples = 4 value = [4, 0] class = No 2138->2142 2140 entropy = 0.0 samples = 1 value = [1, 0] class = No 2139->2140 2141 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2139->2141 2145 YRSWRKPA <= 24.5 entropy = 0.787 samples = 17 value = [4, 13] class = Yes 2144->2145 2154 YRSWRKPA <= 24.0 entropy = 0.722 samples = 5 value = [4, 1] class = No 2144->2154 2146 JNTSYMP_2.0 <= 0.5 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 2145->2146 2153 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2145->2153 2147 BEDDAYR <= 0.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 2146->2147 2152 entropy = 0.0 samples = 2 value = [2, 0] class = No 2146->2152 2148 AHEARST1_4.0 <= 0.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 2147->2148 2151 entropy = 0.0 samples = 1 value = [1, 0] class = No 2147->2151 2149 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2148->2149 2150 entropy = 0.0 samples = 1 value = [1, 0] class = No 2148->2150 2155 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2154->2155 2156 entropy = 0.0 samples = 4 value = [4, 0] class = No 2154->2156 2160 entropy = 0.0 samples = 8 value = [8, 0] class = No 2159->2160 2161 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2159->2161 2163 DOINGLWA_5.0 <= 0.5 entropy = 0.968 samples = 43 value = [26, 17] class = No 2162->2163 2182 YRSWRKPA <= 19.0 entropy = 0.661 samples = 35 value = [29, 6] class = No 2162->2182 2164 BEDDAYR <= 3.0 entropy = 0.877 samples = 27 value = [19, 8] class = No 2163->2164 2175 BMI <= 2330.5 entropy = 0.989 samples = 16 value = [7, 9] class = Yes 2163->2175 2165 YRSWRKPA <= 6.0 entropy = 0.971 samples = 20 value = [12, 8] class = No 2164->2165 2174 entropy = 0.0 samples = 7 value = [7, 0] class = No 2164->2174 2166 AHCNOYR2 <= 3.5 entropy = 0.985 samples = 14 value = [6, 8] class = Yes 2165->2166 2173 entropy = 0.0 samples = 6 value = [6, 0] class = No 2165->2173 2167 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2166->2167 2168 SMKSTAT2_3.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 2166->2168 2169 entropy = 0.0 samples = 5 value = [5, 0] class = No 2168->2169 2170 BEDDAYR <= 1.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2168->2170 2171 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2170->2171 2172 entropy = 0.0 samples = 1 value = [1, 0] class = No 2170->2172 2176 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2175->2176 2177 CHPAIN6M_3.0 <= 0.5 entropy = 0.98 samples = 12 value = [7, 5] class = No 2175->2177 2178 ASIMEDC_2.0 <= 0.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 2177->2178 2181 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2177->2181 2179 entropy = 0.0 samples = 7 value = [7, 0] class = No 2178->2179 2180 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2178->2180 2183 entropy = 0.0 samples = 13 value = [13, 0] class = No 2182->2183 2184 AHCNOYR2 <= 2.5 entropy = 0.845 samples = 22 value = [16, 6] class = No 2182->2184 2185 R_MARITL_4 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 2184->2185 2194 BMI <= 2808.0 entropy = 0.592 samples = 14 value = [12, 2] class = No 2184->2194 2186 ASIMEDC_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 2185->2186 2193 entropy = 0.0 samples = 2 value = [2, 0] class = No 2185->2193 2187 BEDDAYR <= 1.0 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2186->2187 2192 entropy = 0.0 samples = 1 value = [1, 0] class = No 2186->2192 2188 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2187->2188 2189 ASIRETR_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2187->2189 2190 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2189->2190 2191 entropy = 0.0 samples = 1 value = [1, 0] class = No 2189->2191 2195 entropy = 0.0 samples = 10 value = [10, 0] class = No 2194->2195 2196 BEDDAYR <= 2.0 entropy = 1.0 samples = 4 value = [2, 2] class = No 2194->2196 2197 SMKSTAT2_3.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2196->2197 2200 entropy = 0.0 samples = 1 value = [1, 0] class = No 2196->2200 2198 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2197->2198 2199 entropy = 0.0 samples = 1 value = [1, 0] class = No 2197->2199 2202 SMKSTAT2_3.0 <= 0.5 entropy = 0.722 samples = 20 value = [4, 16] class = Yes 2201->2202 2215 HIT1A_2.0 <= 0.5 entropy = 0.989 samples = 16 value = [9, 7] class = No 2201->2215 2203 ASICNHC_4.0 <= 0.5 entropy = 0.89 samples = 13 value = [4, 9] class = Yes 2202->2203 2214 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2202->2214 2204 YRSWRKPA <= 13.0 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 2203->2204 2213 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2203->2213 2205 CHLEV_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 2204->2205 2212 entropy = 0.0 samples = 2 value = [2, 0] class = No 2204->2212 2206 HYPEV_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2205->2206 2211 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2205->2211 2207 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2206->2207 2210 entropy = 0.0 samples = 1 value = [1, 0] class = No 2206->2210 2208 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2207->2208 2209 entropy = 0.0 samples = 1 value = [1, 0] class = No 2207->2209 2216 entropy = 0.0 samples = 6 value = [6, 0] class = No 2215->2216 2217 PAINLB_2.0 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 2215->2217 2218 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2217->2218 2219 BMI <= 3305.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 2217->2219 2220 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2219->2220 2221 BMI <= 3789.0 entropy = 0.811 samples = 4 value = [3, 1] class = No 2219->2221 2222 entropy = 0.0 samples = 3 value = [3, 0] class = No 2221->2222 2223 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2221->2223 2225 DBHVWLY_2.0 <= 0.5 entropy = 0.956 samples = 69 value = [43, 26] class = No 2224->2225 2268 DIBEV1_3.0 <= 0.5 entropy = 0.503 samples = 54 value = [48, 6] class = No 2224->2268 2226 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2225->2226 2227 CHPAIN6M_3.0 <= 0.5 entropy = 0.933 samples = 66 value = [43, 23] class = No 2225->2227 2228 BMI <= 2030.0 entropy = 0.979 samples = 53 value = [31, 22] class = No 2227->2228 2263 SMKSTAT2_3.0 <= 0.5 entropy = 0.391 samples = 13 value = [12, 1] class = No 2227->2263 2229 entropy = 0.0 samples = 4 value = [4, 0] class = No 2228->2229 2230 VIMGLASS_2.0 <= 0.5 entropy = 0.992 samples = 49 value = [27, 22] class = No 2228->2230 2231 BMI <= 2500.5 entropy = 0.995 samples = 35 value = [16, 19] class = Yes 2230->2231 2256 ASICNHC_4.0 <= 0.5 entropy = 0.75 samples = 14 value = [11, 3] class = No 2230->2256 2232 BMI <= 2154.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 2231->2232 2239 BMI <= 2723.5 entropy = 0.918 samples = 24 value = [8, 16] class = Yes 2231->2239 2233 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2232->2233 2234 ASICNHC_2.0 <= 0.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 2232->2234 2235 entropy = 0.0 samples = 7 value = [7, 0] class = No 2234->2235 2236 BMI <= 2233.0 entropy = 1.0 samples = 2 value = [1, 1] class = No 2234->2236 2237 entropy = 0.0 samples = 1 value = [1, 0] class = No 2236->2237 2238 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2236->2238 2240 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2239->2240 2241 BMI <= 2851.0 entropy = 0.971 samples = 20 value = [8, 12] class = Yes 2239->2241 2242 entropy = 0.0 samples = 2 value = [2, 0] class = No 2241->2242 2243 BEDDAYR <= 0.5 entropy = 0.918 samples = 18 value = [6, 12] class = Yes 2241->2243 2244 CHPAIN6M_4.0 <= 0.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 2243->2244 2251 CHLEV_2.0 <= 0.5 entropy = 0.503 samples = 9 value = [1, 8] class = Yes 2243->2251 2245 AHCNOYR2 <= 2.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 2244->2245 2250 entropy = 0.0 samples = 3 value = [3, 0] class = No 2244->2250 2246 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2245->2246 2247 HYPEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2245->2247 2248 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2247->2248 2249 entropy = 0.0 samples = 2 value = [2, 0] class = No 2247->2249 2252 HIT1A_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2251->2252 2255 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2251->2255 2253 entropy = 0.0 samples = 1 value = [1, 0] class = No 2252->2253 2254 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2252->2254 2257 AHCNOYR2 <= 3.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 2256->2257 2262 entropy = 0.0 samples = 6 value = [6, 0] class = No 2256->2262 2258 CHPAIN6M_4.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2257->2258 2261 entropy = 0.0 samples = 4 value = [4, 0] class = No 2257->2261 2259 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2258->2259 2260 entropy = 0.0 samples = 1 value = [1, 0] class = No 2258->2260 2264 entropy = 0.0 samples = 11 value = [11, 0] class = No 2263->2264 2265 HIT1A_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2263->2265 2266 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2265->2266 2267 entropy = 0.0 samples = 1 value = [1, 0] class = No 2265->2267 2269 YRSWRKPA <= 21.0 entropy = 0.323 samples = 51 value = [48, 3] class = No 2268->2269 2282 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2268->2282 2270 JNTSYMP_2.0 <= 0.5 entropy = 0.48 samples = 29 value = [26, 3] class = No 2269->2270 2281 entropy = 0.0 samples = 22 value = [22, 0] class = No 2269->2281 2271 AHCNOYR2 <= 7.5 entropy = 0.61 samples = 20 value = [17, 3] class = No 2270->2271 2280 entropy = 0.0 samples = 9 value = [9, 0] class = No 2270->2280 2272 CHLEV_2.0 <= 0.5 entropy = 0.485 samples = 19 value = [17, 2] class = No 2271->2272 2279 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2271->2279 2273 AMDLONGR_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 2272->2273 2278 entropy = 0.0 samples = 12 value = [12, 0] class = No 2272->2278 2274 DIBREL_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2273->2274 2277 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2273->2277 2275 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2274->2275 2276 entropy = 0.0 samples = 5 value = [5, 0] class = No 2274->2276 2284 BMI <= 2118.0 entropy = 0.193 samples = 101 value = [98, 3] class = No 2283->2284 2295 DIBPRE2_2.0 <= 0.5 entropy = 0.7 samples = 1147 value = [930, 217] class = No 2283->2295 2285 BMI <= 2072.0 entropy = 0.722 samples = 10 value = [8, 2] class = No 2284->2285 2290 BMI <= 3437.5 entropy = 0.087 samples = 91 value = [90, 1] class = No 2284->2290 2286 entropy = 0.0 samples = 7 value = [7, 0] class = No 2285->2286 2287 ASISTLV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2285->2287 2288 entropy = 0.0 samples = 1 value = [1, 0] class = No 2287->2288 2289 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2287->2289 2291 entropy = 0.0 samples = 79 value = [79, 0] class = No 2290->2291 2292 BMI <= 3480.5 entropy = 0.414 samples = 12 value = [11, 1] class = No 2290->2292 2293 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2292->2293 2294 entropy = 0.0 samples = 11 value = [11, 0] class = No 2292->2294 2296 BMI <= 2766.5 entropy = 0.951 samples = 100 value = [63, 37] class = No 2295->2296 2349 HIT1A_2.0 <= 0.5 entropy = 0.662 samples = 1047 value = [867, 180] class = No 2295->2349 2297 BMI <= 2489.5 entropy = 0.827 samples = 50 value = [37, 13] class = No 2296->2297 2324 ASIRETR_4.0 <= 0.5 entropy = 0.999 samples = 50 value = [26, 24] class = No 2296->2324 2298 ASIRETR_2.0 <= 0.5 entropy = 0.999 samples = 23 value = [12, 11] class = No 2297->2298 2315 CHPAIN6M_4.0 <= 0.5 entropy = 0.381 samples = 27 value = [25, 2] class = No 2297->2315 2299 FLUVACYR_2.0 <= 0.5 entropy = 0.971 samples = 20 value = [12, 8] class = No 2298->2299 2314 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2298->2314 2300 JNTSYMP_2.0 <= 0.5 entropy = 0.837 samples = 15 value = [11, 4] class = No 2299->2300 2311 ASICNHC_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2299->2311 2301 DOINGLWA_5.0 <= 0.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 2300->2301 2310 entropy = 0.0 samples = 6 value = [6, 0] class = No 2300->2310 2302 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2301->2302 2303 BMI <= 2457.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 2301->2303 2304 ASISTLV_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 2303->2304 2309 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2303->2309 2305 ASIRETR_4.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2304->2305 2308 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2304->2308 2306 entropy = 0.0 samples = 5 value = [5, 0] class = No 2305->2306 2307 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2305->2307 2312 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2311->2312 2313 entropy = 0.0 samples = 1 value = [1, 0] class = No 2311->2313 2316 entropy = 0.0 samples = 16 value = [16, 0] class = No 2315->2316 2317 FLUVACYR_2.0 <= 0.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 2315->2317 2318 VIMGLASS_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 2317->2318 2323 entropy = 0.0 samples = 5 value = [5, 0] class = No 2317->2323 2319 YRSWRKPA <= 17.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 2318->2319 2322 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2318->2322 2320 entropy = 0.0 samples = 4 value = [4, 0] class = No 2319->2320 2321 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2319->2321 2325 YRSWRKPA <= 31.0 entropy = 0.944 samples = 36 value = [23, 13] class = No 2324->2325 2342 BMI <= 3488.5 entropy = 0.75 samples = 14 value = [3, 11] class = Yes 2324->2342 2326 HIT1A_2.0 <= 0.5 entropy = 0.885 samples = 33 value = [23, 10] class = No 2325->2326 2341 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2325->2341 2327 YRSWRKPA <= 16.5 entropy = 1.0 samples = 16 value = [8, 8] class = No 2326->2327 2336 ASIMEDC_4.0 <= 0.5 entropy = 0.523 samples = 17 value = [15, 2] class = No 2326->2336 2328 CHPAIN6M_4.0 <= 0.5 entropy = 0.961 samples = 13 value = [8, 5] class = No 2327->2328 2335 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2327->2335 2329 YRSWRKPA <= 2.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 2328->2329 2334 entropy = 0.0 samples = 5 value = [5, 0] class = No 2328->2334 2330 BMI <= 3006.0 entropy = 0.811 samples = 4 value = [3, 1] class = No 2329->2330 2333 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2329->2333 2331 entropy = 0.0 samples = 3 value = [3, 0] class = No 2330->2331 2332 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2330->2332 2337 entropy = 0.0 samples = 13 value = [13, 0] class = No 2336->2337 2338 SMKSTAT2_3.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2336->2338 2339 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2338->2339 2340 entropy = 0.0 samples = 2 value = [2, 0] class = No 2338->2340 2343 AHEARST1_4.0 <= 0.5 entropy = 0.439 samples = 11 value = [1, 10] class = Yes 2342->2343 2346 PDSICKA_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2342->2346 2344 entropy = 0.0 samples = 10 value = [0, 10] class = Yes 2343->2344 2345 entropy = 0.0 samples = 1 value = [1, 0] class = No 2343->2345 2347 entropy = 0.0 samples = 2 value = [2, 0] class = No 2346->2347 2348 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2346->2348 2350 BMI <= 2662.5 entropy = 0.758 samples = 448 value = [350, 98] class = No 2349->2350 2535 PAINLB_2.0 <= 0.5 entropy = 0.576 samples = 599 value = [517, 82] class = No 2349->2535 2351 BMI <= 1922.0 entropy = 0.643 samples = 287 value = [240, 47] class = No 2350->2351 2448 PDSICKA_2.0 <= 0.5 entropy = 0.901 samples = 161 value = [110, 51] class = No 2350->2448 2352 entropy = 0.0 samples = 24 value = [24, 0] class = No 2351->2352 2353 BMI <= 2584.5 entropy = 0.677 samples = 263 value = [216, 47] class = No 2351->2353 2354 ASIRETR_2.0 <= 0.5 entropy = 0.712 samples = 236 value = [190, 46] class = No 2353->2354 2443 AHCNOYR2 <= 6.5 entropy = 0.229 samples = 27 value = [26, 1] class = No 2353->2443 2355 AHCNOYR2 <= 3.5 entropy = 0.634 samples = 169 value = [142, 27] class = No 2354->2355 2414 ASISTLV_4.0 <= 0.5 entropy = 0.86 samples = 67 value = [48, 19] class = No 2354->2414 2356 YRSWRKPA <= 6.5 entropy = 0.446 samples = 86 value = [78, 8] class = No 2355->2356 2377 SMKSTAT2_3.0 <= 0.5 entropy = 0.776 samples = 83 value = [64, 19] class = No 2355->2377 2357 entropy = 0.0 samples = 38 value = [38, 0] class = No 2356->2357 2358 CHPAIN6M_4.0 <= 0.5 entropy = 0.65 samples = 48 value = [40, 8] class = No 2356->2358 2359 BMI <= 2102.0 entropy = 0.477 samples = 39 value = [35, 4] class = No 2358->2359 2370 YRSWRKPA <= 29.0 entropy = 0.991 samples = 9 value = [5, 4] class = No 2358->2370 2360 FLUVACYR_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 2359->2360 2363 BMI <= 2496.0 entropy = 0.323 samples = 34 value = [32, 2] class = No 2359->2363 2361 entropy = 0.0 samples = 3 value = [3, 0] class = No 2360->2361 2362 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2360->2362 2364 entropy = 0.0 samples = 28 value = [28, 0] class = No 2363->2364 2365 ARTH1_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 2363->2365 2366 entropy = 0.0 samples = 3 value = [3, 0] class = No 2365->2366 2367 ASISTLV_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2365->2367 2368 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2367->2368 2369 entropy = 0.0 samples = 1 value = [1, 0] class = No 2367->2369 2371 CHLEV_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 2370->2371 2376 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2370->2376 2372 HYBPLEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2371->2372 2375 entropy = 0.0 samples = 4 value = [4, 0] class = No 2371->2375 2373 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2372->2373 2374 entropy = 0.0 samples = 1 value = [1, 0] class = No 2372->2374 2378 DIBREL_2.0 <= 0.5 entropy = 0.87 samples = 55 value = [39, 16] class = No 2377->2378 2405 PDSICKA_2.0 <= 0.5 entropy = 0.491 samples = 28 value = [25, 3] class = No 2377->2405 2379 PDSICKA_2.0 <= 0.5 entropy = 1.0 samples = 14 value = [7, 7] class = No 2378->2379 2388 HYPEV_2.0 <= 0.5 entropy = 0.759 samples = 41 value = [32, 9] class = No 2378->2388 2380 CHPAIN6M_3.0 <= 0.5 entropy = 0.881 samples = 10 value = [7, 3] class = No 2379->2380 2387 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2379->2387 2381 ASISTLV_2.0 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 2380->2381 2386 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2380->2386 2382 entropy = 0.0 samples = 6 value = [6, 0] class = No 2381->2382 2383 ASIMEDC_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2381->2383 2384 entropy = 0.0 samples = 1 value = [1, 0] class = No 2383->2384 2385 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2383->2385 2389 VIMGLASS_2.0 <= 0.5 entropy = 0.989 samples = 16 value = [9, 7] class = No 2388->2389 2400 CHPAIN6M_4.0 <= 0.5 entropy = 0.402 samples = 25 value = [23, 2] class = No 2388->2400 2390 PDSICKA_2.0 <= 0.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 2389->2390 2399 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2389->2399 2391 YRSWRKPA <= 18.0 entropy = 1.0 samples = 8 value = [4, 4] class = No 2390->2391 2398 entropy = 0.0 samples = 5 value = [5, 0] class = No 2390->2398 2392 BMI <= 2336.0 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2391->2392 2397 entropy = 0.0 samples = 3 value = [3, 0] class = No 2391->2397 2393 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2392->2393 2394 BEDDAYR <= 1.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2392->2394 2395 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2394->2395 2396 entropy = 0.0 samples = 1 value = [1, 0] class = No 2394->2396 2401 entropy = 0.0 samples = 20 value = [20, 0] class = No 2400->2401 2402 BEDDAYR <= 8.0 entropy = 0.971 samples = 5 value = [3, 2] class = No 2400->2402 2403 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2402->2403 2404 entropy = 0.0 samples = 3 value = [3, 0] class = No 2402->2404 2406 entropy = 0.0 samples = 13 value = [13, 0] class = No 2405->2406 2407 ASIMEDC_4.0 <= 0.5 entropy = 0.722 samples = 15 value = [12, 3] class = No 2405->2407 2408 AHEARST1_4.0 <= 0.5 entropy = 0.414 samples = 12 value = [11, 1] class = No 2407->2408 2411 PAINLB_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2407->2411 2409 entropy = 0.0 samples = 11 value = [11, 0] class = No 2408->2409 2410 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2408->2410 2412 entropy = 0.0 samples = 1 value = [1, 0] class = No 2411->2412 2413 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2411->2413 2415 BMI <= 2571.5 entropy = 0.768 samples = 58 value = [45, 13] class = No 2414->2415 2440 YRSWRKPA <= 3.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 2414->2440 2416 BMI <= 2080.5 entropy = 0.691 samples = 54 value = [44, 10] class = No 2415->2416 2437 ARTH1_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2415->2437 2417 BMI <= 2042.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 2416->2417 2420 AHCNOYR2 <= 6.5 entropy = 0.592 samples = 49 value = [42, 7] class = No 2416->2420 2418 entropy = 0.0 samples = 2 value = [2, 0] class = No 2417->2418 2419 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2417->2419 2421 BMI <= 2159.0 entropy = 0.689 samples = 38 value = [31, 7] class = No 2420->2421 2436 entropy = 0.0 samples = 11 value = [11, 0] class = No 2420->2436 2422 entropy = 0.0 samples = 9 value = [9, 0] class = No 2421->2422 2423 BMI <= 2249.5 entropy = 0.797 samples = 29 value = [22, 7] class = No 2421->2423 2424 BEDDAYR <= 4.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2423->2424 2429 ASICNHC_2.0 <= 0.5 entropy = 0.575 samples = 22 value = [19, 3] class = No 2423->2429 2425 JNTSYMP_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 2424->2425 2428 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2424->2428 2426 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2425->2426 2427 entropy = 0.0 samples = 3 value = [3, 0] class = No 2425->2427 2430 entropy = 0.0 samples = 14 value = [14, 0] class = No 2429->2430 2431 ARTH1_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 2429->2431 2432 BMI <= 2533.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2431->2432 2435 entropy = 0.0 samples = 4 value = [4, 0] class = No 2431->2435 2433 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2432->2433 2434 entropy = 0.0 samples = 1 value = [1, 0] class = No 2432->2434 2438 entropy = 0.0 samples = 1 value = [1, 0] class = No 2437->2438 2439 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2437->2439 2441 entropy = 0.0 samples = 3 value = [3, 0] class = No 2440->2441 2442 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2440->2442 2444 entropy = 0.0 samples = 21 value = [21, 0] class = No 2443->2444 2445 AHCNOYR2 <= 7.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2443->2445 2446 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2445->2446 2447 entropy = 0.0 samples = 5 value = [5, 0] class = No 2445->2447 2449 AHCNOYR2 <= 1.5 entropy = 0.971 samples = 95 value = [57, 38] class = No 2448->2449 2514 VIMGLASS_2.0 <= 0.5 entropy = 0.716 samples = 66 value = [53, 13] class = No 2448->2514 2450 entropy = 0.0 samples = 6 value = [6, 0] class = No 2449->2450 2451 AHEARST1_4.0 <= 0.5 entropy = 0.985 samples = 89 value = [51, 38] class = No 2449->2451 2452 YRSWRKPA <= 3.5 entropy = 0.97 samples = 83 value = [50, 33] class = No 2451->2452 2511 AHCNOYR2 <= 6.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 2451->2511 2453 ASICNHC_2.0 <= 0.5 entropy = 0.982 samples = 19 value = [8, 11] class = Yes 2452->2453 2466 ASISTLV_2.0 <= 0.5 entropy = 0.928 samples = 64 value = [42, 22] class = No 2452->2466 2454 CHPAIN6M_3.0 <= 0.5 entropy = 0.997 samples = 15 value = [8, 7] class = No 2453->2454 2465 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2453->2465 2455 ASIRETR_4.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2454->2455 2458 VIMGLASS_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 2454->2458 2456 entropy = 0.0 samples = 5 value = [5, 0] class = No 2455->2456 2457 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2455->2457 2459 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2458->2459 2460 R_MARITL_4 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 2458->2460 2461 DIBREL_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2460->2461 2464 entropy = 0.0 samples = 2 value = [2, 0] class = No 2460->2464 2462 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2461->2462 2463 entropy = 0.0 samples = 1 value = [1, 0] class = No 2461->2463 2467 YRSWRKPA <= 4.5 entropy = 0.98 samples = 48 value = [28, 20] class = No 2466->2467 2506 YRSWRKPA <= 6.5 entropy = 0.544 samples = 16 value = [14, 2] class = No 2466->2506 2468 entropy = 0.0 samples = 3 value = [3, 0] class = No 2467->2468 2469 BEDDAYR <= 29.0 entropy = 0.991 samples = 45 value = [25, 20] class = No 2467->2469 2470 AHCNOYR2 <= 4.5 entropy = 0.996 samples = 43 value = [23, 20] class = No 2469->2470 2505 entropy = 0.0 samples = 2 value = [2, 0] class = No 2469->2505 2471 CHPAIN6M_4.0 <= 0.5 entropy = 0.948 samples = 30 value = [19, 11] class = No 2470->2471 2494 CHLEV_2.0 <= 0.5 entropy = 0.89 samples = 13 value = [4, 9] class = Yes 2470->2494 2472 BMI <= 3247.5 entropy = 0.983 samples = 26 value = [15, 11] class = No 2471->2472 2493 entropy = 0.0 samples = 4 value = [4, 0] class = No 2471->2493 2473 BMI <= 3051.5 entropy = 0.998 samples = 19 value = [9, 10] class = Yes 2472->2473 2488 BEDDAYR <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 2472->2488 2474 ASIRETR_4.0 <= 0.5 entropy = 0.989 samples = 16 value = [9, 7] class = No 2473->2474 2487 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2473->2487 2475 VIMGLASS_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2474->2475 2480 JNTSYMP_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 2474->2480 2476 entropy = 0.0 samples = 4 value = [4, 0] class = No 2475->2476 2477 DOINGLWA_5.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2475->2477 2478 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2477->2478 2479 entropy = 0.0 samples = 1 value = [1, 0] class = No 2477->2479 2481 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2480->2481 2482 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 2480->2482 2483 entropy = 0.0 samples = 3 value = [3, 0] class = No 2482->2483 2484 AHSTATYR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2482->2484 2485 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2484->2485 2486 entropy = 0.0 samples = 1 value = [1, 0] class = No 2484->2486 2489 entropy = 0.0 samples = 5 value = [5, 0] class = No 2488->2489 2490 BMI <= 3427.0 entropy = 1.0 samples = 2 value = [1, 1] class = No 2488->2490 2491 entropy = 0.0 samples = 1 value = [1, 0] class = No 2490->2491 2492 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2490->2492 2495 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2494->2495 2496 YRSWRKPA <= 13.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 2494->2496 2497 entropy = 0.0 samples = 2 value = [2, 0] class = No 2496->2497 2498 BMI <= 2722.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 2496->2498 2499 entropy = 0.0 samples = 1 value = [1, 0] class = No 2498->2499 2500 HYPEV_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2498->2500 2501 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2500->2501 2502 AHCNOYR2 <= 5.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2500->2502 2503 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2502->2503 2504 entropy = 0.0 samples = 1 value = [1, 0] class = No 2502->2504 2507 ASIMEDC_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2506->2507 2510 entropy = 0.0 samples = 13 value = [13, 0] class = No 2506->2510 2508 entropy = 0.0 samples = 1 value = [1, 0] class = No 2507->2508 2509 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2507->2509 2512 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2511->2512 2513 entropy = 0.0 samples = 1 value = [1, 0] class = No 2511->2513 2515 WRKLYR4_2.0 <= 0.5 entropy = 0.843 samples = 48 value = [35, 13] class = No 2514->2515 2534 entropy = 0.0 samples = 18 value = [18, 0] class = No 2514->2534 2516 JNTSYMP_2.0 <= 0.5 entropy = 0.998 samples = 21 value = [10, 11] class = Yes 2515->2516 2529 AHCNOYR2 <= 7.5 entropy = 0.381 samples = 27 value = [25, 2] class = No 2515->2529 2517 YRSWRKPA <= 13.5 entropy = 0.722 samples = 10 value = [2, 8] class = Yes 2516->2517 2522 BMI <= 3403.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 2516->2522 2518 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 2517->2518 2519 BMI <= 2713.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2517->2519 2520 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2519->2520 2521 entropy = 0.0 samples = 2 value = [2, 0] class = No 2519->2521 2523 entropy = 0.0 samples = 5 value = [5, 0] class = No 2522->2523 2524 BEDDAYR <= 1.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 2522->2524 2525 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2524->2525 2526 BMI <= 3701.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 2524->2526 2527 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2526->2527 2528 entropy = 0.0 samples = 3 value = [3, 0] class = No 2526->2528 2530 entropy = 0.0 samples = 23 value = [23, 0] class = No 2529->2530 2531 BEDDAYR <= 45.0 entropy = 1.0 samples = 4 value = [2, 2] class = No 2529->2531 2532 entropy = 0.0 samples = 2 value = [2, 0] class = No 2531->2532 2533 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2531->2533 2536 BMI <= 1859.0 entropy = 0.684 samples = 264 value = [216, 48] class = No 2535->2536 2631 CHPAIN6M_4.0 <= 0.5 entropy = 0.474 samples = 335 value = [301, 34] class = No 2535->2631 2537 AHCNOYR2 <= 2.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2536->2537 2540 BEDDAYR <= 42.5 entropy = 0.665 samples = 260 value = [215, 45] class = No 2536->2540 2538 entropy = 0.0 samples = 1 value = [1, 0] class = No 2537->2538 2539 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2537->2539 2541 BMI <= 4174.5 entropy = 0.629 samples = 241 value = [203, 38] class = No 2540->2541 2622 VIMGLASS_2.0 <= 0.5 entropy = 0.949 samples = 19 value = [12, 7] class = No 2540->2622 2542 ASISTLV_2.0 <= 0.5 entropy = 0.62 samples = 240 value = [203, 37] class = No 2541->2542 2621 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2541->2621 2543 BMI <= 2642.5 entropy = 0.681 samples = 183 value = [150, 33] class = No 2542->2543 2610 BMI <= 2165.5 entropy = 0.367 samples = 57 value = [53, 4] class = No 2542->2610 2544 JNTSYMP_2.0 <= 0.5 entropy = 0.493 samples = 102 value = [91, 11] class = No 2543->2544 2569 YRSWRKPA <= 30.5 entropy = 0.844 samples = 81 value = [59, 22] class = No 2543->2569 2545 BEDDAYR <= 0.5 entropy = 0.303 samples = 74 value = [70, 4] class = No 2544->2545 2556 AHCNOYR2 <= 3.5 entropy = 0.811 samples = 28 value = [21, 7] class = No 2544->2556 2546 YRSWRKPA <= 2.5 entropy = 0.439 samples = 44 value = [40, 4] class = No 2545->2546 2555 entropy = 0.0 samples = 30 value = [30, 0] class = No 2545->2555 2547 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2546->2547 2548 DOINGLWA_5.0 <= 0.5 entropy = 0.276 samples = 42 value = [40, 2] class = No 2546->2548 2549 BMI <= 2295.0 entropy = 0.764 samples = 9 value = [7, 2] class = No 2548->2549 2554 entropy = 0.0 samples = 33 value = [33, 0] class = No 2548->2554 2550 BMI <= 2222.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2549->2550 2553 entropy = 0.0 samples = 5 value = [5, 0] class = No 2549->2553 2551 entropy = 0.0 samples = 2 value = [2, 0] class = No 2550->2551 2552 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2550->2552 2557 BMI <= 2556.5 entropy = 0.323 samples = 17 value = [16, 1] class = No 2556->2557 2562 BMI <= 2475.0 entropy = 0.994 samples = 11 value = [5, 6] class = Yes 2556->2562 2558 entropy = 0.0 samples = 15 value = [15, 0] class = No 2557->2558 2559 AHCNOYR2 <= 2.0 entropy = 1.0 samples = 2 value = [1, 1] class = No 2557->2559 2560 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2559->2560 2561 entropy = 0.0 samples = 1 value = [1, 0] class = No 2559->2561 2563 YRSWRKPA <= 17.5 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 2562->2563 2568 entropy = 0.0 samples = 3 value = [3, 0] class = No 2562->2568 2564 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2563->2564 2565 YRSWRKPA <= 27.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2563->2565 2566 entropy = 0.0 samples = 2 value = [2, 0] class = No 2565->2566 2567 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2565->2567 2570 YRSWRKPA <= 19.5 entropy = 0.893 samples = 71 value = [49, 22] class = No 2569->2570 2609 entropy = 0.0 samples = 10 value = [10, 0] class = No 2569->2609 2571 CHPAIN6M_3.0 <= 0.5 entropy = 0.675 samples = 45 value = [37, 8] class = No 2570->2571 2594 VIMGLASS_2.0 <= 0.5 entropy = 0.996 samples = 26 value = [12, 14] class = Yes 2570->2594 2572 PDSICKA_2.0 <= 0.5 entropy = 0.494 samples = 37 value = [33, 4] class = No 2571->2572 2589 ASIMEDC_4.0 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 2571->2589 2573 HYBPLEV_2.0 <= 0.5 entropy = 0.779 samples = 13 value = [10, 3] class = No 2572->2573 2584 AMDLONGR_1.0 <= 0.5 entropy = 0.25 samples = 24 value = [23, 1] class = No 2572->2584 2574 AHCNOYR2 <= 3.5 entropy = 0.65 samples = 12 value = [10, 2] class = No 2573->2574 2583 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2573->2583 2575 entropy = 0.0 samples = 6 value = [6, 0] class = No 2574->2575 2576 BMI <= 3465.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 2574->2576 2577 ASIRETR_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 2576->2577 2582 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2576->2582 2578 entropy = 0.0 samples = 3 value = [3, 0] class = No 2577->2578 2579 CHLEV_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2577->2579 2580 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2579->2580 2581 entropy = 0.0 samples = 1 value = [1, 0] class = No 2579->2581 2585 BEDDAYR <= 2.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2584->2585 2588 entropy = 0.0 samples = 21 value = [21, 0] class = No 2584->2588 2586 entropy = 0.0 samples = 2 value = [2, 0] class = No 2585->2586 2587 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2585->2587 2590 ASIRETR_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2589->2590 2593 entropy = 0.0 samples = 3 value = [3, 0] class = No 2589->2593 2591 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2590->2591 2592 entropy = 0.0 samples = 1 value = [1, 0] class = No 2590->2592 2595 BMI <= 2734.0 entropy = 0.946 samples = 22 value = [8, 14] class = Yes 2594->2595 2608 entropy = 0.0 samples = 4 value = [4, 0] class = No 2594->2608 2596 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2595->2596 2597 ASISTLV_4.0 <= 0.5 entropy = 0.991 samples = 18 value = [8, 10] class = Yes 2595->2597 2598 HYBPLEV_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 2597->2598 2603 AHCNOYR2 <= 3.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 2597->2603 2599 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2598->2599 2600 R_MARITL_4 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2598->2600 2601 entropy = 0.0 samples = 1 value = [1, 0] class = No 2600->2601 2602 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2600->2602 2604 WRKLYR4_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 2603->2604 2607 entropy = 0.0 samples = 5 value = [5, 0] class = No 2603->2607 2605 entropy = 0.0 samples = 2 value = [2, 0] class = No 2604->2605 2606 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2604->2606 2611 AHCNOYR2 <= 3.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 2610->2611 2616 YRSWRKPA <= 32.5 entropy = 0.137 samples = 52 value = [51, 1] class = No 2610->2616 2612 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2611->2612 2613 ASIMEDC_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2611->2613 2614 entropy = 0.0 samples = 2 value = [2, 0] class = No 2613->2614 2615 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2613->2615 2617 entropy = 0.0 samples = 50 value = [50, 0] class = No 2616->2617 2618 ASIMEDC_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2616->2618 2619 entropy = 0.0 samples = 1 value = [1, 0] class = No 2618->2619 2620 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2618->2620 2623 ASIRETR_2.0 <= 0.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 2622->2623 2630 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2622->2630 2624 DIBREL_2.0 <= 0.5 entropy = 0.592 samples = 14 value = [12, 2] class = No 2623->2624 2629 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2623->2629 2625 PDSICKA_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 2624->2625 2628 entropy = 0.0 samples = 9 value = [9, 0] class = No 2624->2628 2626 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2625->2626 2627 entropy = 0.0 samples = 3 value = [3, 0] class = No 2625->2627 2632 BEDDAYR <= 2.5 entropy = 0.521 samples = 282 value = [249, 33] class = No 2631->2632 2713 AHCNOYR2 <= 1.5 entropy = 0.135 samples = 53 value = [52, 1] class = No 2631->2713 2633 FLUVACYR_2.0 <= 0.5 entropy = 0.56 samples = 237 value = [206, 31] class = No 2632->2633 2708 YRSWRKPA <= 32.0 entropy = 0.262 samples = 45 value = [43, 2] class = No 2632->2708 2634 BMI <= 2256.0 entropy = 0.476 samples = 137 value = [123, 14] class = No 2633->2634 2671 BMI <= 2145.0 entropy = 0.658 samples = 100 value = [83, 17] class = No 2633->2671 2635 entropy = 0.0 samples = 23 value = [23, 0] class = No 2634->2635 2636 YRSWRKPA <= 3.5 entropy = 0.537 samples = 114 value = [100, 14] class = No 2634->2636 2637 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 15 value = [10, 5] class = No 2636->2637 2646 YRSWRKPA <= 11.5 entropy = 0.439 samples = 99 value = [90, 9] class = No 2636->2646 2638 WRKLYR4_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2637->2638 2641 VIMGLASS_2.0 <= 0.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 2637->2641 2639 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2638->2639 2640 entropy = 0.0 samples = 1 value = [1, 0] class = No 2638->2640 2642 entropy = 0.0 samples = 8 value = [8, 0] class = No 2641->2642 2643 DOINGLWA_5.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2641->2643 2644 entropy = 0.0 samples = 1 value = [1, 0] class = No 2643->2644 2645 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2643->2645 2647 entropy = 0.0 samples = 16 value = [16, 0] class = No 2646->2647 2648 ASIRETR_2.0 <= 0.5 entropy = 0.495 samples = 83 value = [74, 9] class = No 2646->2648 2649 YRSWRKPA <= 27.0 entropy = 0.379 samples = 68 value = [63, 5] class = No 2648->2649 2664 YRSWRKPA <= 22.0 entropy = 0.837 samples = 15 value = [11, 4] class = No 2648->2664 2650 entropy = 0.0 samples = 34 value = [34, 0] class = No 2649->2650 2651 HYBPLEV_2.0 <= 0.5 entropy = 0.602 samples = 34 value = [29, 5] class = No 2649->2651 2652 ARTH1_2.0 <= 0.5 entropy = 0.449 samples = 32 value = [29, 3] class = No 2651->2652 2663 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2651->2663 2653 BMI <= 2651.0 entropy = 0.75 samples = 14 value = [11, 3] class = No 2652->2653 2662 entropy = 0.0 samples = 18 value = [18, 0] class = No 2652->2662 2654 entropy = 0.0 samples = 5 value = [5, 0] class = No 2653->2654 2655 BMI <= 2693.0 entropy = 0.918 samples = 9 value = [6, 3] class = No 2653->2655 2656 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2655->2656 2657 SMKSTAT2_3.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 2655->2657 2658 ASISTLV_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2657->2658 2661 entropy = 0.0 samples = 5 value = [5, 0] class = No 2657->2661 2659 entropy = 0.0 samples = 1 value = [1, 0] class = No 2658->2659 2660 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2658->2660 2665 ASICNHC_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2664->2665 2670 entropy = 0.0 samples = 10 value = [10, 0] class = No 2664->2670 2666 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2665->2666 2667 BMI <= 2673.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2665->2667 2668 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2667->2668 2669 entropy = 0.0 samples = 1 value = [1, 0] class = No 2667->2669 2672 BMI <= 2034.5 entropy = 0.996 samples = 13 value = [7, 6] class = No 2671->2672 2679 R_MARITL_4 <= 0.5 entropy = 0.548 samples = 87 value = [76, 11] class = No 2671->2679 2673 BMI <= 1929.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 2672->2673 2678 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2672->2678 2674 ASIMEDC_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2673->2674 2677 entropy = 0.0 samples = 6 value = [6, 0] class = No 2673->2677 2675 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2674->2675 2676 entropy = 0.0 samples = 1 value = [1, 0] class = No 2674->2676 2680 YRSWRKPA <= 33.5 entropy = 0.633 samples = 69 value = [58, 11] class = No 2679->2680 2707 entropy = 0.0 samples = 18 value = [18, 0] class = No 2679->2707 2681 BMI <= 2246.5 entropy = 0.681 samples = 61 value = [50, 11] class = No 2680->2681 2706 entropy = 0.0 samples = 8 value = [8, 0] class = No 2680->2706 2682 entropy = 0.0 samples = 6 value = [6, 0] class = No 2681->2682 2683 BMI <= 2372.0 entropy = 0.722 samples = 55 value = [44, 11] class = No 2681->2683 2684 DOINGLWA_5.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 2683->2684 2687 BMI <= 2561.5 entropy = 0.634 samples = 50 value = [42, 8] class = No 2683->2687 2685 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2684->2685 2686 entropy = 0.0 samples = 2 value = [2, 0] class = No 2684->2686 2688 entropy = 0.0 samples = 9 value = [9, 0] class = No 2687->2688 2689 BMI <= 2719.5 entropy = 0.712 samples = 41 value = [33, 8] class = No 2687->2689 2690 CHPAIN6M_3.0 <= 0.5 entropy = 0.918 samples = 15 value = [10, 5] class = No 2689->2690 2697 AHCNOYR2 <= 2.5 entropy = 0.516 samples = 26 value = [23, 3] class = No 2689->2697 2691 BMI <= 2700.5 entropy = 0.779 samples = 13 value = [10, 3] class = No 2690->2691 2696 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2690->2696 2692 YRSWRKPA <= 31.0 entropy = 0.439 samples = 11 value = [10, 1] class = No 2691->2692 2695 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2691->2695 2693 entropy = 0.0 samples = 10 value = [10, 0] class = No 2692->2693 2694 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2692->2694 2698 entropy = 0.0 samples = 16 value = [16, 0] class = No 2697->2698 2699 BMI <= 2861.0 entropy = 0.881 samples = 10 value = [7, 3] class = No 2697->2699 2700 entropy = 0.0 samples = 5 value = [5, 0] class = No 2699->2700 2701 JNTSYMP_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 2699->2701 2702 ASIRETR_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2701->2702 2705 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2701->2705 2703 entropy = 0.0 samples = 2 value = [2, 0] class = No 2702->2703 2704 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2702->2704 2709 entropy = 0.0 samples = 40 value = [40, 0] class = No 2708->2709 2710 BMI <= 2587.0 entropy = 0.971 samples = 5 value = [3, 2] class = No 2708->2710 2711 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2710->2711 2712 entropy = 0.0 samples = 3 value = [3, 0] class = No 2710->2712 2714 DOINGLWA_5.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2713->2714 2717 entropy = 0.0 samples = 47 value = [47, 0] class = No 2713->2717 2715 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2714->2715 2716 entropy = 0.0 samples = 5 value = [5, 0] class = No 2714->2716 2719 AMDLONGR_1.0 <= 0.5 entropy = 0.663 samples = 3311 value = [2740, 571] class = No 2718->2719 3908 AHCNOYR2 <= 0.5 entropy = 0.409 samples = 2876 value = [2640, 236] class = No 2718->3908 2720 AHCNOYR2 <= 1.5 entropy = 0.45 samples = 967 value = [876, 91] class = No 2719->2720 2947 BMI <= 3193.5 entropy = 0.731 samples = 2344 value = [1864, 480] class = No 2719->2947 2721 BMI <= 3843.5 entropy = 0.347 samples = 692 value = [647, 45] class = No 2720->2721 2840 BMI <= 2507.0 entropy = 0.651 samples = 275 value = [229, 46] class = No 2720->2840 2722 YRSWRKPA <= 5.5 entropy = 0.327 samples = 685 value = [644, 41] class = No 2721->2722 2835 VIMGLASS_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2721->2835 2723 DOINGLWA_5.0 <= 0.5 entropy = 0.221 samples = 396 value = [382, 14] class = No 2722->2723 2772 BEDDAYR <= 0.5 entropy = 0.448 samples = 289 value = [262, 27] class = No 2722->2772 2724 BMI <= 3128.5 entropy = 0.173 samples = 349 value = [340, 9] class = No 2723->2724 2761 CHLEV_2.0 <= 0.5 entropy = 0.489 samples = 47 value = [42, 5] class = No 2723->2761 2725 ASIRETR_4.0 <= 0.5 entropy = 0.137 samples = 311 value = [305, 6] class = No 2724->2725 2754 BMI <= 3144.0 entropy = 0.398 samples = 38 value = [35, 3] class = No 2724->2754 2726 YRSWRKPA <= 3.5 entropy = 0.177 samples = 225 value = [219, 6] class = No 2725->2726 2753 entropy = 0.0 samples = 86 value = [86, 0] class = No 2725->2753 2727 PAINLB_2.0 <= 0.5 entropy = 0.122 samples = 181 value = [178, 3] class = No 2726->2727 2740 BEDDAYR <= 1.5 entropy = 0.359 samples = 44 value = [41, 3] class = No 2726->2740 2728 R_MARITL_4 <= 0.5 entropy = 0.353 samples = 30 value = [28, 2] class = No 2727->2728 2735 ARTH1_2.0 <= 0.5 entropy = 0.057 samples = 151 value = [150, 1] class = No 2727->2735 2729 BMI <= 2898.0 entropy = 0.684 samples = 11 value = [9, 2] class = No 2728->2729 2734 entropy = 0.0 samples = 19 value = [19, 0] class = No 2728->2734 2730 ASICNHC_2.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 2729->2730 2733 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2729->2733 2731 entropy = 0.0 samples = 9 value = [9, 0] class = No 2730->2731 2732 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2730->2732 2736 PDSICKA_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 2735->2736 2739 entropy = 0.0 samples = 146 value = [146, 0] class = No 2735->2739 2737 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2736->2737 2738 entropy = 0.0 samples = 4 value = [4, 0] class = No 2736->2738 2741 BMI <= 2511.0 entropy = 0.179 samples = 37 value = [36, 1] class = No 2740->2741 2748 AMDLONGR_3.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 2740->2748 2742 entropy = 0.0 samples = 20 value = [20, 0] class = No 2741->2742 2743 BMI <= 2532.5 entropy = 0.323 samples = 17 value = [16, 1] class = No 2741->2743 2744 ASIMEDC_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2743->2744 2747 entropy = 0.0 samples = 15 value = [15, 0] class = No 2743->2747 2745 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2744->2745 2746 entropy = 0.0 samples = 1 value = [1, 0] class = No 2744->2746 2749 PDSICKA_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2748->2749 2752 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2748->2752 2750 entropy = 0.0 samples = 5 value = [5, 0] class = No 2749->2750 2751 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2749->2751 2755 PDSICKA_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2754->2755 2758 BEDDAYR <= 2.5 entropy = 0.187 samples = 35 value = [34, 1] class = No 2754->2758 2756 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2755->2756 2757 entropy = 0.0 samples = 1 value = [1, 0] class = No 2755->2757 2759 entropy = 0.0 samples = 34 value = [34, 0] class = No 2758->2759 2760 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2758->2760 2762 BMI <= 2552.0 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 2761->2762 2765 JNTSYMP_2.0 <= 0.5 entropy = 0.276 samples = 42 value = [40, 2] class = No 2761->2765 2763 entropy = 0.0 samples = 2 value = [2, 0] class = No 2762->2763 2764 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2762->2764 2766 DBHVCLN_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 2765->2766 2771 entropy = 0.0 samples = 35 value = [35, 0] class = No 2765->2771 2767 entropy = 0.0 samples = 4 value = [4, 0] class = No 2766->2767 2768 DIBREL_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2766->2768 2769 entropy = 0.0 samples = 1 value = [1, 0] class = No 2768->2769 2770 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2768->2770 2773 DIBREL_2.0 <= 0.5 entropy = 0.313 samples = 230 value = [217, 13] class = No 2772->2773 2810 BMI <= 2979.5 entropy = 0.791 samples = 59 value = [45, 14] class = No 2772->2810 2774 BMI <= 3399.0 entropy = 0.579 samples = 58 value = [50, 8] class = No 2773->2774 2795 BMI <= 2646.0 entropy = 0.19 samples = 172 value = [167, 5] class = No 2773->2795 2775 YRSWRKPA <= 19.5 entropy = 0.445 samples = 54 value = [49, 5] class = No 2774->2775 2790 BMI <= 3478.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2774->2790 2776 ASIMEDC_4.0 <= 0.5 entropy = 0.179 samples = 37 value = [36, 1] class = No 2775->2776 2781 HIT1A_2.0 <= 0.5 entropy = 0.787 samples = 17 value = [13, 4] class = No 2775->2781 2777 entropy = 0.0 samples = 29 value = [29, 0] class = No 2776->2777 2778 YRSWRKPA <= 8.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 2776->2778 2779 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2778->2779 2780 entropy = 0.0 samples = 7 value = [7, 0] class = No 2778->2780 2782 BMI <= 2265.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 2781->2782 2785 DBHVCLN_2.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 2781->2785 2783 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2782->2783 2784 entropy = 0.0 samples = 10 value = [10, 0] class = No 2782->2784 2786 AHCNOYR2 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 2785->2786 2789 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2785->2789 2787 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2786->2787 2788 entropy = 0.0 samples = 3 value = [3, 0] class = No 2786->2788 2791 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2790->2791 2792 HYPEV_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2790->2792 2793 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2792->2793 2794 entropy = 0.0 samples = 1 value = [1, 0] class = No 2792->2794 2796 entropy = 0.0 samples = 91 value = [91, 0] class = No 2795->2796 2797 YRSWRKPA <= 29.5 entropy = 0.334 samples = 81 value = [76, 5] class = No 2795->2797 2798 BMI <= 2653.5 entropy = 0.183 samples = 72 value = [70, 2] class = No 2797->2798 2805 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 2797->2805 2799 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2798->2799 2800 YRSWRKPA <= 6.5 entropy = 0.107 samples = 71 value = [70, 1] class = No 2798->2800 2801 DOINGLWA_5.0 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 2800->2801 2804 entropy = 0.0 samples = 63 value = [63, 0] class = No 2800->2804 2802 entropy = 0.0 samples = 7 value = [7, 0] class = No 2801->2802 2803 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2801->2803 2806 PAINLB_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 2805->2806 2809 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2805->2809 2807 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2806->2807 2808 entropy = 0.0 samples = 6 value = [6, 0] class = No 2806->2808 2811 CHPAIN6M_3.0 <= 0.5 entropy = 0.863 samples = 49 value = [35, 14] class = No 2810->2811 2834 entropy = 0.0 samples = 10 value = [10, 0] class = No 2810->2834 2812 BMI <= 2754.5 entropy = 0.82 samples = 47 value = [35, 12] class = No 2811->2812 2833 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2811->2833 2813 AMDLONGR_2.0 <= 0.5 entropy = 0.602 samples = 34 value = [29, 5] class = No 2812->2813 2826 ASIMEDC_4.0 <= 0.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 2812->2826 2814 entropy = 0.0 samples = 15 value = [15, 0] class = No 2813->2814 2815 YRSWRKPA <= 25.5 entropy = 0.831 samples = 19 value = [14, 5] class = No 2813->2815 2816 BEDDAYR <= 4.0 entropy = 0.764 samples = 18 value = [14, 4] class = No 2815->2816 2825 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2815->2825 2817 ASICNHC_2.0 <= 0.5 entropy = 0.672 samples = 17 value = [14, 3] class = No 2816->2817 2824 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2816->2824 2818 R_MARITL_4 <= 0.5 entropy = 0.544 samples = 16 value = [14, 2] class = No 2817->2818 2823 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2817->2823 2819 entropy = 0.0 samples = 12 value = [12, 0] class = No 2818->2819 2820 PDSICKA_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2818->2820 2821 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2820->2821 2822 entropy = 0.0 samples = 2 value = [2, 0] class = No 2820->2822 2827 DIBREL_2.0 <= 0.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 2826->2827 2832 entropy = 0.0 samples = 5 value = [5, 0] class = No 2826->2832 2828 DBHVWLY_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2827->2828 2831 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 2827->2831 2829 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2828->2829 2830 entropy = 0.0 samples = 1 value = [1, 0] class = No 2828->2830 2836 JNTSYMP_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2835->2836 2839 entropy = 0.0 samples = 2 value = [2, 0] class = No 2835->2839 2837 entropy = 0.0 samples = 1 value = [1, 0] class = No 2836->2837 2838 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2836->2838 2841 DIBPRE2_2.0 <= 0.5 entropy = 0.416 samples = 131 value = [120, 11] class = No 2840->2841 2874 BEDDAYR <= 2.5 entropy = 0.8 samples = 144 value = [109, 35] class = No 2840->2874 2842 SMKSTAT2_3.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 2841->2842 2845 YRSWRKPA <= 12.5 entropy = 0.369 samples = 127 value = [118, 9] class = No 2841->2845 2843 entropy = 0.0 samples = 2 value = [2, 0] class = No 2842->2843 2844 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2842->2844 2846 YRSWRKPA <= 3.5 entropy = 0.449 samples = 96 value = [87, 9] class = No 2845->2846 2873 entropy = 0.0 samples = 31 value = [31, 0] class = No 2845->2873 2847 AHCNOYR2 <= 2.5 entropy = 0.216 samples = 58 value = [56, 2] class = No 2846->2847 2858 YRSWRKPA <= 4.5 entropy = 0.689 samples = 38 value = [31, 7] class = No 2846->2858 2848 entropy = 0.0 samples = 46 value = [46, 0] class = No 2847->2848 2849 WRKLYR4_2.0 <= 0.5 entropy = 0.65 samples = 12 value = [10, 2] class = No 2847->2849 2850 DIBREL_2.0 <= 0.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 2849->2850 2857 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2849->2857 2851 AHCNOYR2 <= 3.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 2850->2851 2856 entropy = 0.0 samples = 7 value = [7, 0] class = No 2850->2856 2852 DBHVCLN_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2851->2852 2855 entropy = 0.0 samples = 2 value = [2, 0] class = No 2851->2855 2853 entropy = 0.0 samples = 1 value = [1, 0] class = No 2852->2853 2854 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2852->2854 2859 BEDDAYR <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2858->2859 2864 YRSWRKPA <= 11.5 entropy = 0.459 samples = 31 value = [28, 3] class = No 2858->2864 2860 CHLEV_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 2859->2860 2863 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2859->2863 2861 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2860->2861 2862 entropy = 0.0 samples = 3 value = [3, 0] class = No 2860->2862 2865 ASIRETR_2.0 <= 0.5 entropy = 0.353 samples = 30 value = [28, 2] class = No 2864->2865 2872 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2864->2872 2866 entropy = 0.0 samples = 23 value = [23, 0] class = No 2865->2866 2867 BMI <= 2091.0 entropy = 0.863 samples = 7 value = [5, 2] class = No 2865->2867 2868 ASISTLV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2867->2868 2871 entropy = 0.0 samples = 4 value = [4, 0] class = No 2867->2871 2869 entropy = 0.0 samples = 1 value = [1, 0] class = No 2868->2869 2870 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2868->2870 2875 YRSWRKPA <= 0.5 entropy = 0.831 samples = 133 value = [98, 35] class = No 2874->2875 2946 entropy = 0.0 samples = 11 value = [11, 0] class = No 2874->2946 2876 DBHVCLN_2.0 <= 0.5 entropy = 0.994 samples = 22 value = [12, 10] class = No 2875->2876 2893 PDSICKA_2.0 <= 0.5 entropy = 0.77 samples = 111 value = [86, 25] class = No 2875->2893 2877 DOINGLWA_5.0 <= 0.5 entropy = 0.971 samples = 20 value = [12, 8] class = No 2876->2877 2892 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2876->2892 2878 ASISTLV_4.0 <= 0.5 entropy = 0.837 samples = 15 value = [11, 4] class = No 2877->2878 2889 PAINLB_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2877->2889 2879 BMI <= 2662.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 2878->2879 2888 entropy = 0.0 samples = 6 value = [6, 0] class = No 2878->2888 2880 entropy = 0.0 samples = 2 value = [2, 0] class = No 2879->2880 2881 AHCNOYR2 <= 2.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2879->2881 2882 BMI <= 3372.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 2881->2882 2887 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2881->2887 2883 BMI <= 2913.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2882->2883 2886 entropy = 0.0 samples = 2 value = [2, 0] class = No 2882->2886 2884 entropy = 0.0 samples = 1 value = [1, 0] class = No 2883->2884 2885 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2883->2885 2890 entropy = 0.0 samples = 1 value = [1, 0] class = No 2889->2890 2891 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2889->2891 2894 YRSWRKPA <= 1.5 entropy = 0.856 samples = 82 value = [59, 23] class = No 2893->2894 2939 ASISTLV_2.0 <= 0.5 entropy = 0.362 samples = 29 value = [27, 2] class = No 2893->2939 2895 entropy = 0.0 samples = 7 value = [7, 0] class = No 2894->2895 2896 CHLEV_2.0 <= 0.5 entropy = 0.889 samples = 75 value = [52, 23] class = No 2894->2896 2897 PAINLB_2.0 <= 0.5 entropy = 0.998 samples = 21 value = [11, 10] class = No 2896->2897 2912 AHCNOYR2 <= 2.5 entropy = 0.796 samples = 54 value = [41, 13] class = No 2896->2912 2898 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2897->2898 2899 YRSWRKPA <= 7.5 entropy = 0.964 samples = 18 value = [11, 7] class = No 2897->2899 2900 ASIRETR_4.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2899->2900 2903 DIBREL_2.0 <= 0.5 entropy = 0.863 samples = 14 value = [10, 4] class = No 2899->2903 2901 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2900->2901 2902 entropy = 0.0 samples = 1 value = [1, 0] class = No 2900->2902 2904 JNTSYMP_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 2903->2904 2907 YRSWRKPA <= 31.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 2903->2907 2905 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2904->2905 2906 entropy = 0.0 samples = 2 value = [2, 0] class = No 2904->2906 2908 entropy = 0.0 samples = 7 value = [7, 0] class = No 2907->2908 2909 ASIRETR_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 2907->2909 2910 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2909->2910 2911 entropy = 0.0 samples = 1 value = [1, 0] class = No 2909->2911 2913 R_MARITL_4 <= 0.5 entropy = 0.851 samples = 47 value = [34, 13] class = No 2912->2913 2938 entropy = 0.0 samples = 7 value = [7, 0] class = No 2912->2938 2914 YRSWRKPA <= 24.0 entropy = 0.722 samples = 35 value = [28, 7] class = No 2913->2914 2931 BEDDAYR <= 0.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 2913->2931 2915 YRSWRKPA <= 12.5 entropy = 0.555 samples = 31 value = [27, 4] class = No 2914->2915 2928 PAINLB_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2914->2928 2916 BMI <= 2533.0 entropy = 0.722 samples = 20 value = [16, 4] class = No 2915->2916 2927 entropy = 0.0 samples = 11 value = [11, 0] class = No 2915->2927 2917 VIMGLASS_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2916->2917 2920 YRSWRKPA <= 5.5 entropy = 0.523 samples = 17 value = [15, 2] class = No 2916->2920 2918 entropy = 0.0 samples = 1 value = [1, 0] class = No 2917->2918 2919 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2917->2919 2921 entropy = 0.0 samples = 9 value = [9, 0] class = No 2920->2921 2922 BMI <= 2744.0 entropy = 0.811 samples = 8 value = [6, 2] class = No 2920->2922 2923 entropy = 0.0 samples = 5 value = [5, 0] class = No 2922->2923 2924 HIT1A_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2922->2924 2925 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2924->2925 2926 entropy = 0.0 samples = 1 value = [1, 0] class = No 2924->2926 2929 entropy = 0.0 samples = 1 value = [1, 0] class = No 2928->2929 2930 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2928->2930 2932 BMI <= 2886.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 2931->2932 2937 entropy = 0.0 samples = 3 value = [3, 0] class = No 2931->2937 2933 YRSWRKPA <= 3.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 2932->2933 2936 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2932->2936 2934 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2933->2934 2935 entropy = 0.0 samples = 3 value = [3, 0] class = No 2933->2935 2940 entropy = 0.0 samples = 22 value = [22, 0] class = No 2939->2940 2941 BMI <= 2883.0 entropy = 0.863 samples = 7 value = [5, 2] class = No 2939->2941 2942 entropy = 0.0 samples = 4 value = [4, 0] class = No 2941->2942 2943 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 2941->2943 2944 entropy = 0.0 samples = 1 value = [1, 0] class = No 2943->2944 2945 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 2943->2945 2948 YRSWRKPA <= 9.5 entropy = 0.695 samples = 2065 value = [1679, 386] class = No 2947->2948 3763 PDSICKA_2.0 <= 0.5 entropy = 0.922 samples = 279 value = [185, 94] class = No 2947->3763 2949 CHLEV_2.0 <= 0.5 entropy = 0.624 samples = 1240 value = [1047, 193] class = No 2948->2949 3396 FLUVACYR_2.0 <= 0.5 entropy = 0.785 samples = 825 value = [632, 193] class = No 2948->3396 2950 HYBPLEV_2.0 <= 0.5 entropy = 0.816 samples = 166 value = [124, 42] class = No 2949->2950 3031 DBHVCLN_2.0 <= 0.5 entropy = 0.586 samples = 1074 value = [923, 151] class = No 2949->3031 2951 YRSWRKPA <= 2.5 entropy = 0.759 samples = 155 value = [121, 34] class = No 2950->2951 3024 SMKSTAT2_3.0 <= 0.5 entropy = 0.845 samples = 11 value = [3, 8] class = Yes 2950->3024 2952 AHCNOYR2 <= 2.5 entropy = 0.889 samples = 75 value = [52, 23] class = No 2951->2952 2993 DOINGLWA_5.0 <= 0.5 entropy = 0.578 samples = 80 value = [69, 11] class = No 2951->2993 2953 BMI <= 2693.5 entropy = 0.684 samples = 44 value = [36, 8] class = No 2952->2953 2972 CHPAIN6M_4.0 <= 0.5 entropy = 0.999 samples = 31 value = [16, 15] class = No 2952->2972 2954 FLUVACYR_2.0 <= 0.5 entropy = 0.381 samples = 27 value = [25, 2] class = No 2953->2954 2963 BMI <= 2928.0 entropy = 0.937 samples = 17 value = [11, 6] class = No 2953->2963 2955 entropy = 0.0 samples = 14 value = [14, 0] class = No 2954->2955 2956 YRSWRKPA <= 1.5 entropy = 0.619 samples = 13 value = [11, 2] class = No 2954->2956 2957 AHCNOYR2 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 2956->2957 2962 entropy = 0.0 samples = 6 value = [6, 0] class = No 2956->2962 2958 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2957->2958 2959 DIBREL_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2957->2959 2960 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2959->2960 2961 entropy = 0.0 samples = 5 value = [5, 0] class = No 2959->2961 2964 JNTSYMP_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 2963->2964 2971 entropy = 0.0 samples = 7 value = [7, 0] class = No 2963->2971 2965 entropy = 0.0 samples = 2 value = [2, 0] class = No 2964->2965 2966 R_MARITL_4 <= 0.5 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 2964->2966 2967 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2966->2967 2968 DOINGLWA_5.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 2966->2968 2969 entropy = 0.0 samples = 2 value = [2, 0] class = No 2968->2969 2970 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2968->2970 2973 AHCNOYR2 <= 3.5 entropy = 0.991 samples = 27 value = [12, 15] class = Yes 2972->2973 2992 entropy = 0.0 samples = 4 value = [4, 0] class = No 2972->2992 2974 ASICNHC_4.0 <= 0.5 entropy = 0.961 samples = 13 value = [8, 5] class = No 2973->2974 2983 BEDDAYR <= 1.5 entropy = 0.863 samples = 14 value = [4, 10] class = Yes 2973->2983 2975 ASIMEDC_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 2974->2975 2978 PAINLB_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 2974->2978 2976 entropy = 0.0 samples = 5 value = [5, 0] class = No 2975->2976 2977 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2975->2977 2979 entropy = 0.0 samples = 2 value = [2, 0] class = No 2978->2979 2980 AHEARST1_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 2978->2980 2981 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 2980->2981 2982 entropy = 0.0 samples = 1 value = [1, 0] class = No 2980->2982 2984 ASIMEDC_4.0 <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 2983->2984 2991 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2983->2991 2985 DOINGLWA_5.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 2984->2985 2990 entropy = 0.0 samples = 2 value = [2, 0] class = No 2984->2990 2986 BEDDAYR <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 2985->2986 2989 entropy = 0.0 samples = 1 value = [1, 0] class = No 2985->2989 2987 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 2986->2987 2988 entropy = 0.0 samples = 1 value = [1, 0] class = No 2986->2988 2994 PAINLB_2.0 <= 0.5 entropy = 0.662 samples = 64 value = [53, 11] class = No 2993->2994 3023 entropy = 0.0 samples = 16 value = [16, 0] class = No 2993->3023 2995 entropy = 0.0 samples = 11 value = [11, 0] class = No 2994->2995 2996 BMI <= 3142.5 entropy = 0.737 samples = 53 value = [42, 11] class = No 2994->2996 2997 BEDDAYR <= 1.5 entropy = 0.706 samples = 52 value = [42, 10] class = No 2996->2997 3022 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 2996->3022 2998 ARTH1_2.0 <= 0.5 entropy = 0.782 samples = 43 value = [33, 10] class = No 2997->2998 3021 entropy = 0.0 samples = 9 value = [9, 0] class = No 2997->3021 2999 ASISTLV_4.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 2998->2999 3002 BMI <= 2735.5 entropy = 0.679 samples = 39 value = [32, 7] class = No 2998->3002 3000 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 2999->3000 3001 entropy = 0.0 samples = 1 value = [1, 0] class = No 2999->3001 3003 ASIRETR_2.0 <= 0.5 entropy = 0.84 samples = 26 value = [19, 7] class = No 3002->3003 3020 entropy = 0.0 samples = 13 value = [13, 0] class = No 3002->3020 3004 DIBPRE2_2.0 <= 0.5 entropy = 0.949 samples = 19 value = [12, 7] class = No 3003->3004 3019 entropy = 0.0 samples = 7 value = [7, 0] class = No 3003->3019 3005 ASICNHC_4.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3004->3005 3008 BMI <= 2642.5 entropy = 0.837 samples = 15 value = [11, 4] class = No 3004->3008 3006 entropy = 0.0 samples = 1 value = [1, 0] class = No 3005->3006 3007 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3005->3007 3009 HIT1A_2.0 <= 0.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 3008->3009 3018 entropy = 0.0 samples = 4 value = [4, 0] class = No 3008->3018 3010 JNTSYMP_2.0 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 3009->3010 3017 entropy = 0.0 samples = 3 value = [3, 0] class = No 3009->3017 3011 entropy = 0.0 samples = 2 value = [2, 0] class = No 3010->3011 3012 DBHVCLN_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 3010->3012 3013 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3012->3013 3014 AHCNOYR2 <= 2.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3012->3014 3015 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3014->3015 3016 entropy = 0.0 samples = 2 value = [2, 0] class = No 3014->3016 3025 DIBREL_2.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3024->3025 3030 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 3024->3030 3026 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3025->3026 3027 VIMGLASS_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 3025->3027 3028 entropy = 0.0 samples = 3 value = [3, 0] class = No 3027->3028 3029 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3027->3029 3032 DBHVWLY_2.0 <= 0.5 entropy = 0.51 samples = 618 value = [548, 70] class = No 3031->3032 3217 AHCNOYR2 <= 5.5 entropy = 0.675 samples = 456 value = [375, 81] class = No 3031->3217 3033 FLUVACYR_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 3032->3033 3038 HYBPLEV_2.0 <= 0.5 entropy = 0.498 samples = 613 value = [546, 67] class = No 3032->3038 3034 PAINLB_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3033->3034 3037 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3033->3037 3035 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3034->3035 3036 entropy = 0.0 samples = 2 value = [2, 0] class = No 3034->3036 3039 WRKLYR4_2.0 <= 0.5 entropy = 0.474 samples = 590 value = [530, 60] class = No 3038->3039 3202 YRSWRKPA <= 0.5 entropy = 0.887 samples = 23 value = [16, 7] class = No 3038->3202 3040 ASIRETR_4.0 <= 0.5 entropy = 0.434 samples = 527 value = [480, 47] class = No 3039->3040 3177 SMKSTAT2_3.0 <= 0.5 entropy = 0.734 samples = 63 value = [50, 13] class = No 3039->3177 3041 BEDDAYR <= 4.5 entropy = 0.497 samples = 385 value = [343, 42] class = No 3040->3041 3152 YRSWRKPA <= 1.5 entropy = 0.22 samples = 142 value = [137, 5] class = No 3040->3152 3042 HIT1A_2.0 <= 0.5 entropy = 0.512 samples = 368 value = [326, 42] class = No 3041->3042 3151 entropy = 0.0 samples = 17 value = [17, 0] class = No 3041->3151 3043 BMI <= 2569.5 entropy = 0.556 samples = 278 value = [242, 36] class = No 3042->3043 3130 PDSICKA_2.0 <= 0.5 entropy = 0.353 samples = 90 value = [84, 6] class = No 3042->3130 3044 YRSWRKPA <= 5.5 entropy = 0.454 samples = 147 value = [133, 14] class = No 3043->3044 3081 BMI <= 2655.5 entropy = 0.653 samples = 131 value = [109, 22] class = No 3043->3081 3045 YRSWRKPA <= 3.5 entropy = 0.361 samples = 131 value = [122, 9] class = No 3044->3045 3072 AHCNOYR2 <= 2.5 entropy = 0.896 samples = 16 value = [11, 5] class = No 3044->3072 3046 ASISTLV_2.0 <= 0.5 entropy = 0.411 samples = 109 value = [100, 9] class = No 3045->3046 3071 entropy = 0.0 samples = 22 value = [22, 0] class = No 3045->3071 3047 BMI <= 2424.0 entropy = 0.32 samples = 86 value = [81, 5] class = No 3046->3047 3064 ARTH1_2.0 <= 0.5 entropy = 0.667 samples = 23 value = [19, 4] class = No 3046->3064 3048 BMI <= 2411.5 entropy = 0.409 samples = 61 value = [56, 5] class = No 3047->3048 3063 entropy = 0.0 samples = 25 value = [25, 0] class = No 3047->3063 3049 BMI <= 2291.5 entropy = 0.297 samples = 57 value = [54, 3] class = No 3048->3049 3060 AHCNOYR2 <= 1.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 3048->3060 3050 BMI <= 2253.0 entropy = 0.431 samples = 34 value = [31, 3] class = No 3049->3050 3059 entropy = 0.0 samples = 23 value = [23, 0] class = No 3049->3059 3051 AHCNOYR2 <= 7.5 entropy = 0.222 samples = 28 value = [27, 1] class = No 3050->3051 3056 VIMGLASS_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 3050->3056 3052 entropy = 0.0 samples = 26 value = [26, 0] class = No 3051->3052 3053 ASIMEDC_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3051->3053 3054 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3053->3054 3055 entropy = 0.0 samples = 1 value = [1, 0] class = No 3053->3055 3057 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3056->3057 3058 entropy = 0.0 samples = 4 value = [4, 0] class = No 3056->3058 3061 entropy = 0.0 samples = 2 value = [2, 0] class = No 3060->3061 3062 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3060->3062 3065 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3064->3065 3066 BEDDAYR <= 1.5 entropy = 0.454 samples = 21 value = [19, 2] class = No 3064->3066 3067 entropy = 0.0 samples = 17 value = [17, 0] class = No 3066->3067 3068 R_MARITL_4 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 3066->3068 3069 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3068->3069 3070 entropy = 0.0 samples = 2 value = [2, 0] class = No 3068->3070 3073 YRSWRKPA <= 6.5 entropy = 0.994 samples = 11 value = [6, 5] class = No 3072->3073 3080 entropy = 0.0 samples = 5 value = [5, 0] class = No 3072->3080 3074 ASIMEDC_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 3073->3074 3077 ARTH1_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3073->3077 3075 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3074->3075 3076 entropy = 0.0 samples = 1 value = [1, 0] class = No 3074->3076 3078 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3077->3078 3079 entropy = 0.0 samples = 5 value = [5, 0] class = No 3077->3079 3082 ASICNHC_4.0 <= 0.5 entropy = 0.932 samples = 23 value = [15, 8] class = No 3081->3082 3095 AHSTATYR_2.0 <= 0.5 entropy = 0.556 samples = 108 value = [94, 14] class = No 3081->3095 3083 BEDDAYR <= 0.5 entropy = 0.991 samples = 18 value = [10, 8] class = No 3082->3083 3094 entropy = 0.0 samples = 5 value = [5, 0] class = No 3082->3094 3084 FLUVACYR_2.0 <= 0.5 entropy = 0.811 samples = 12 value = [9, 3] class = No 3083->3084 3089 ASICNHC_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 3083->3089 3085 PDSICKA_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 3084->3085 3088 entropy = 0.0 samples = 7 value = [7, 0] class = No 3084->3088 3086 entropy = 0.0 samples = 2 value = [2, 0] class = No 3085->3086 3087 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3085->3087 3090 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3089->3090 3091 VIMGLASS_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3089->3091 3092 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3091->3092 3093 entropy = 0.0 samples = 1 value = [1, 0] class = No 3091->3093 3096 PAINLB_2.0 <= 0.5 entropy = 0.534 samples = 107 value = [94, 13] class = No 3095->3096 3129 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3095->3129 3097 entropy = 0.0 samples = 20 value = [20, 0] class = No 3096->3097 3098 YRSWRKPA <= 3.5 entropy = 0.608 samples = 87 value = [74, 13] class = No 3096->3098 3099 BMI <= 2932.0 entropy = 0.391 samples = 52 value = [48, 4] class = No 3098->3099 3110 BEDDAYR <= 0.5 entropy = 0.822 samples = 35 value = [26, 9] class = No 3098->3110 3100 AHCNOYR2 <= 2.5 entropy = 0.579 samples = 29 value = [25, 4] class = No 3099->3100 3109 entropy = 0.0 samples = 23 value = [23, 0] class = No 3099->3109 3101 R_MARITL_4 <= 0.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 3100->3101 3108 entropy = 0.0 samples = 13 value = [13, 0] class = No 3100->3108 3102 FLUVACYR_2.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 3101->3102 3107 entropy = 0.0 samples = 6 value = [6, 0] class = No 3101->3107 3103 ASICNHC_4.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 3102->3103 3106 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3102->3106 3104 entropy = 0.0 samples = 6 value = [6, 0] class = No 3103->3104 3105 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3103->3105 3111 JNTSYMP_2.0 <= 0.5 entropy = 0.634 samples = 25 value = [21, 4] class = No 3110->3111 3122 BMI <= 2874.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 3110->3122 3112 BMI <= 3085.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3111->3112 3117 YRSWRKPA <= 4.5 entropy = 0.297 samples = 19 value = [18, 1] class = No 3111->3117 3113 VIMGLASS_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 3112->3113 3116 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3112->3116 3114 entropy = 0.0 samples = 3 value = [3, 0] class = No 3113->3114 3115 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3113->3115 3118 BMI <= 2762.0 entropy = 0.65 samples = 6 value = [5, 1] class = No 3117->3118 3121 entropy = 0.0 samples = 13 value = [13, 0] class = No 3117->3121 3119 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3118->3119 3120 entropy = 0.0 samples = 5 value = [5, 0] class = No 3118->3120 3123 BMI <= 2682.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 3122->3123 3128 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3122->3128 3124 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3123->3124 3127 entropy = 0.0 samples = 4 value = [4, 0] class = No 3123->3127 3125 entropy = 0.0 samples = 1 value = [1, 0] class = No 3124->3125 3126 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3124->3126 3131 BMI <= 2119.0 entropy = 0.139 samples = 51 value = [50, 1] class = No 3130->3131 3136 DIBPRE2_2.0 <= 0.5 entropy = 0.552 samples = 39 value = [34, 5] class = No 3130->3136 3132 BMI <= 2112.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3131->3132 3135 entropy = 0.0 samples = 45 value = [45, 0] class = No 3131->3135 3133 entropy = 0.0 samples = 5 value = [5, 0] class = No 3132->3133 3134 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3132->3134 3137 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3136->3137 3138 BMI <= 2930.5 entropy = 0.485 samples = 38 value = [34, 4] class = No 3136->3138 3139 BMI <= 2387.0 entropy = 0.323 samples = 34 value = [32, 2] class = No 3138->3139 3146 PAINLB_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 3138->3146 3140 ASICNHC_4.0 <= 0.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 3139->3140 3145 entropy = 0.0 samples = 25 value = [25, 0] class = No 3139->3145 3141 R_MARITL_4 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3140->3141 3144 entropy = 0.0 samples = 6 value = [6, 0] class = No 3140->3144 3142 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3141->3142 3143 entropy = 0.0 samples = 1 value = [1, 0] class = No 3141->3143 3147 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3146->3147 3148 BMI <= 2966.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 3146->3148 3149 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3148->3149 3150 entropy = 0.0 samples = 2 value = [2, 0] class = No 3148->3150 3153 BMI <= 2622.0 entropy = 0.349 samples = 61 value = [57, 4] class = No 3152->3153 3170 AHCNOYR2 <= 4.5 entropy = 0.096 samples = 81 value = [80, 1] class = No 3152->3170 3154 BMI <= 2599.0 entropy = 0.477 samples = 39 value = [35, 4] class = No 3153->3154 3169 entropy = 0.0 samples = 22 value = [22, 0] class = No 3153->3169 3155 BEDDAYR <= 0.5 entropy = 0.398 samples = 38 value = [35, 3] class = No 3154->3155 3168 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3154->3168 3156 HIT1A_2.0 <= 0.5 entropy = 0.529 samples = 25 value = [22, 3] class = No 3155->3156 3167 entropy = 0.0 samples = 13 value = [13, 0] class = No 3155->3167 3157 DOINGLWA_5.0 <= 0.5 entropy = 0.696 samples = 16 value = [13, 3] class = No 3156->3157 3166 entropy = 0.0 samples = 9 value = [9, 0] class = No 3156->3166 3158 YRSWRKPA <= 0.5 entropy = 0.567 samples = 15 value = [13, 2] class = No 3157->3158 3165 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3157->3165 3159 entropy = 0.0 samples = 8 value = [8, 0] class = No 3158->3159 3160 SMKSTAT2_3.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 3158->3160 3161 BMI <= 2238.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3160->3161 3164 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3160->3164 3162 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3161->3162 3163 entropy = 0.0 samples = 5 value = [5, 0] class = No 3161->3163 3171 entropy = 0.0 samples = 71 value = [71, 0] class = No 3170->3171 3172 BMI <= 2854.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 3170->3172 3173 entropy = 0.0 samples = 8 value = [8, 0] class = No 3172->3173 3174 JNTSYMP_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3172->3174 3175 entropy = 0.0 samples = 1 value = [1, 0] class = No 3174->3175 3176 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3174->3176 3178 PAINLB_2.0 <= 0.5 entropy = 0.827 samples = 50 value = [37, 13] class = No 3177->3178 3201 entropy = 0.0 samples = 13 value = [13, 0] class = No 3177->3201 3179 BMI <= 2775.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 3178->3179 3188 PDSICKA_2.0 <= 0.5 entropy = 0.639 samples = 37 value = [31, 6] class = No 3178->3188 3180 ASICNHC_4.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 3179->3180 3187 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3179->3187 3181 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3180->3181 3182 YRSWRKPA <= 3.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 3180->3182 3183 AHCNOYR2 <= 3.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 3182->3183 3186 entropy = 0.0 samples = 4 value = [4, 0] class = No 3182->3186 3184 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3183->3184 3185 entropy = 0.0 samples = 2 value = [2, 0] class = No 3183->3185 3189 entropy = 0.0 samples = 14 value = [14, 0] class = No 3188->3189 3190 BMI <= 2657.5 entropy = 0.828 samples = 23 value = [17, 6] class = No 3188->3190 3191 ASIMEDC_2.0 <= 0.5 entropy = 0.954 samples = 16 value = [10, 6] class = No 3190->3191 3200 entropy = 0.0 samples = 7 value = [7, 0] class = No 3190->3200 3192 AHCNOYR2 <= 2.5 entropy = 0.779 samples = 13 value = [10, 3] class = No 3191->3192 3199 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3191->3199 3193 entropy = 0.0 samples = 8 value = [8, 0] class = No 3192->3193 3194 AHCNOYR2 <= 4.0 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 3192->3194 3195 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3194->3195 3196 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3194->3196 3197 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3196->3197 3198 entropy = 0.0 samples = 2 value = [2, 0] class = No 3196->3198 3203 entropy = 0.0 samples = 6 value = [6, 0] class = No 3202->3203 3204 BMI <= 2224.5 entropy = 0.977 samples = 17 value = [10, 7] class = No 3202->3204 3205 entropy = 0.0 samples = 4 value = [4, 0] class = No 3204->3205 3206 ASIRETR_2.0 <= 0.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 3204->3206 3207 ASICNHC_2.0 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 3206->3207 3216 entropy = 0.0 samples = 3 value = [3, 0] class = No 3206->3216 3208 BMI <= 2431.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 3207->3208 3215 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3207->3215 3209 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3208->3209 3210 BEDDAYR <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3208->3210 3211 BMI <= 2681.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3210->3211 3214 entropy = 0.0 samples = 2 value = [2, 0] class = No 3210->3214 3212 entropy = 0.0 samples = 1 value = [1, 0] class = No 3211->3212 3213 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3211->3213 3218 ASICNHC_4.0 <= 0.5 entropy = 0.607 samples = 390 value = [332, 58] class = No 3217->3218 3361 BMI <= 2672.5 entropy = 0.933 samples = 66 value = [43, 23] class = No 3217->3361 3219 PDSICKA_2.0 <= 0.5 entropy = 0.724 samples = 169 value = [135, 34] class = No 3218->3219 3298 ASIMEDC_2.0 <= 0.5 entropy = 0.496 samples = 221 value = [197, 24] class = No 3218->3298 3220 DOINGLWA_5.0 <= 0.5 entropy = 0.824 samples = 93 value = [69, 24] class = No 3219->3220 3273 DIBPRE2_2.0 <= 0.5 entropy = 0.562 samples = 76 value = [66, 10] class = No 3219->3273 3221 BMI <= 2928.0 entropy = 0.771 samples = 84 value = [65, 19] class = No 3220->3221 3266 YRSWRKPA <= 2.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 3220->3266 3222 BMI <= 2727.5 entropy = 0.705 samples = 73 value = [59, 14] class = No 3221->3222 3259 YRSWRKPA <= 0.5 entropy = 0.994 samples = 11 value = [6, 5] class = No 3221->3259 3223 ASISTLV_4.0 <= 0.5 entropy = 0.758 samples = 64 value = [50, 14] class = No 3222->3223 3258 entropy = 0.0 samples = 9 value = [9, 0] class = No 3222->3258 3224 BEDDAYR <= 0.5 entropy = 0.797 samples = 58 value = [44, 14] class = No 3223->3224 3257 entropy = 0.0 samples = 6 value = [6, 0] class = No 3223->3257 3225 FLUVACYR_2.0 <= 0.5 entropy = 0.579 samples = 29 value = [25, 4] class = No 3224->3225 3238 AHCNOYR2 <= 1.5 entropy = 0.929 samples = 29 value = [19, 10] class = No 3224->3238 3226 entropy = 0.0 samples = 13 value = [13, 0] class = No 3225->3226 3227 BMI <= 1803.0 entropy = 0.811 samples = 16 value = [12, 4] class = No 3225->3227 3228 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3227->3228 3229 VIMGLASS_2.0 <= 0.5 entropy = 0.722 samples = 15 value = [12, 3] class = No 3227->3229 3230 BMI <= 2114.0 entropy = 0.918 samples = 9 value = [6, 3] class = No 3229->3230 3237 entropy = 0.0 samples = 6 value = [6, 0] class = No 3229->3237 3231 entropy = 0.0 samples = 3 value = [3, 0] class = No 3230->3231 3232 SMKSTAT2_3.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3230->3232 3233 YRSWRKPA <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3232->3233 3236 entropy = 0.0 samples = 2 value = [2, 0] class = No 3232->3236 3234 entropy = 0.0 samples = 1 value = [1, 0] class = No 3233->3234 3235 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3233->3235 3239 entropy = 0.0 samples = 5 value = [5, 0] class = No 3238->3239 3240 BMI <= 1928.0 entropy = 0.98 samples = 24 value = [14, 10] class = No 3238->3240 3241 entropy = 0.0 samples = 4 value = [4, 0] class = No 3240->3241 3242 SMKSTAT2_3.0 <= 0.5 entropy = 1.0 samples = 20 value = [10, 10] class = No 3240->3242 3243 ASICNHC_2.0 <= 0.5 entropy = 0.977 samples = 17 value = [10, 7] class = No 3242->3243 3256 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3242->3256 3244 BMI <= 2131.0 entropy = 1.0 samples = 14 value = [7, 7] class = No 3243->3244 3255 entropy = 0.0 samples = 3 value = [3, 0] class = No 3243->3255 3245 entropy = 0.0 samples = 2 value = [2, 0] class = No 3244->3245 3246 BMI <= 2591.5 entropy = 0.98 samples = 12 value = [5, 7] class = Yes 3244->3246 3247 JNTSYMP_2.0 <= 0.5 entropy = 0.881 samples = 10 value = [3, 7] class = Yes 3246->3247 3254 entropy = 0.0 samples = 2 value = [2, 0] class = No 3246->3254 3248 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3247->3248 3249 PAINLB_2.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3247->3249 3250 entropy = 0.0 samples = 2 value = [2, 0] class = No 3249->3250 3251 ASIRETR_4.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3249->3251 3252 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3251->3252 3253 entropy = 0.0 samples = 1 value = [1, 0] class = No 3251->3253 3260 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3259->3260 3261 VIMGLASS_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 3259->3261 3262 entropy = 0.0 samples = 4 value = [4, 0] class = No 3261->3262 3263 YRSWRKPA <= 1.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 3261->3263 3264 entropy = 0.0 samples = 2 value = [2, 0] class = No 3263->3264 3265 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3263->3265 3267 AHCNOYR2 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 3266->3267 3272 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3266->3272 3268 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3267->3268 3269 WRKLYR4_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 3267->3269 3270 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3269->3270 3271 entropy = 0.0 samples = 4 value = [4, 0] class = No 3269->3271 3274 DOINGLWA_5.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3273->3274 3277 PAINLB_2.0 <= 0.5 entropy = 0.469 samples = 70 value = [63, 7] class = No 3273->3277 3275 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3274->3275 3276 entropy = 0.0 samples = 3 value = [3, 0] class = No 3274->3276 3278 ASICNHC_2.0 <= 0.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 3277->3278 3285 YRSWRKPA <= 8.5 entropy = 0.297 samples = 57 value = [54, 3] class = No 3277->3285 3279 AHCNOYR2 <= 4.0 entropy = 0.503 samples = 9 value = [8, 1] class = No 3278->3279 3282 DIBREL_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3278->3282 3280 entropy = 0.0 samples = 8 value = [8, 0] class = No 3279->3280 3281 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3279->3281 3283 entropy = 0.0 samples = 1 value = [1, 0] class = No 3282->3283 3284 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3282->3284 3286 HIT1A_2.0 <= 0.5 entropy = 0.225 samples = 55 value = [53, 2] class = No 3285->3286 3295 DIBREL_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3285->3295 3287 entropy = 0.0 samples = 36 value = [36, 0] class = No 3286->3287 3288 ASISTLV_4.0 <= 0.5 entropy = 0.485 samples = 19 value = [17, 2] class = No 3286->3288 3289 AHCNOYR2 <= 1.5 entropy = 0.31 samples = 18 value = [17, 1] class = No 3288->3289 3294 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3288->3294 3290 YRSWRKPA <= 4.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 3289->3290 3293 entropy = 0.0 samples = 15 value = [15, 0] class = No 3289->3293 3291 entropy = 0.0 samples = 2 value = [2, 0] class = No 3290->3291 3292 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3290->3292 3296 entropy = 0.0 samples = 1 value = [1, 0] class = No 3295->3296 3297 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3295->3297 3299 BMI <= 2178.0 entropy = 0.423 samples = 186 value = [170, 16] class = No 3298->3299 3346 YRSWRKPA <= 3.5 entropy = 0.776 samples = 35 value = [27, 8] class = No 3298->3346 3300 BMI <= 2028.0 entropy = 0.612 samples = 53 value = [45, 8] class = No 3299->3300 3319 SMKSTAT2_3.0 <= 0.5 entropy = 0.328 samples = 133 value = [125, 8] class = No 3299->3319 3301 ASIRETR_2.0 <= 0.5 entropy = 0.235 samples = 26 value = [25, 1] class = No 3300->3301 3306 YRSWRKPA <= 1.5 entropy = 0.826 samples = 27 value = [20, 7] class = No 3300->3306 3302 entropy = 0.0 samples = 22 value = [22, 0] class = No 3301->3302 3303 YRSWRKPA <= 2.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 3301->3303 3304 entropy = 0.0 samples = 3 value = [3, 0] class = No 3303->3304 3305 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3303->3305 3307 BMI <= 2104.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 3306->3307 3316 BMI <= 2048.5 entropy = 0.323 samples = 17 value = [16, 1] class = No 3306->3316 3308 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3307->3308 3309 BEDDAYR <= 7.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 3307->3309 3310 ASIMEDC_4.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 3309->3310 3315 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3309->3315 3311 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3310->3311 3312 WRKLYR4_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 3310->3312 3313 entropy = 0.0 samples = 4 value = [4, 0] class = No 3312->3313 3314 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3312->3314 3317 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3316->3317 3318 entropy = 0.0 samples = 16 value = [16, 0] class = No 3316->3318 3320 YRSWRKPA <= 1.5 entropy = 0.182 samples = 109 value = [106, 3] class = No 3319->3320 3335 BMI <= 2862.0 entropy = 0.738 samples = 24 value = [19, 5] class = No 3319->3335 3321 entropy = 0.0 samples = 56 value = [56, 0] class = No 3320->3321 3322 R_MARITL_4 <= 0.5 entropy = 0.314 samples = 53 value = [50, 3] class = No 3320->3322 3323 entropy = 0.0 samples = 30 value = [30, 0] class = No 3322->3323 3324 HIT1A_2.0 <= 0.5 entropy = 0.559 samples = 23 value = [20, 3] class = No 3322->3324 3325 PAINLB_2.0 <= 0.5 entropy = 0.31 samples = 18 value = [17, 1] class = No 3324->3325 3330 BMI <= 2342.0 entropy = 0.971 samples = 5 value = [3, 2] class = No 3324->3330 3326 ASIRETR_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3325->3326 3329 entropy = 0.0 samples = 15 value = [15, 0] class = No 3325->3329 3327 entropy = 0.0 samples = 2 value = [2, 0] class = No 3326->3327 3328 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3326->3328 3331 entropy = 0.0 samples = 2 value = [2, 0] class = No 3330->3331 3332 HYBPLEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3330->3332 3333 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3332->3333 3334 entropy = 0.0 samples = 1 value = [1, 0] class = No 3332->3334 3336 DIBPRE2_2.0 <= 0.5 entropy = 0.575 samples = 22 value = [19, 3] class = No 3335->3336 3345 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3335->3345 3337 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3336->3337 3338 PAINLB_2.0 <= 0.5 entropy = 0.454 samples = 21 value = [19, 2] class = No 3336->3338 3339 JNTSYMP_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 3338->3339 3344 entropy = 0.0 samples = 14 value = [14, 0] class = No 3338->3344 3340 entropy = 0.0 samples = 4 value = [4, 0] class = No 3339->3340 3341 DOINGLWA_5.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3339->3341 3342 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3341->3342 3343 entropy = 0.0 samples = 1 value = [1, 0] class = No 3341->3343 3347 AHSTATYR_2.0 <= 0.5 entropy = 0.414 samples = 24 value = [22, 2] class = No 3346->3347 3354 BMI <= 2024.0 entropy = 0.994 samples = 11 value = [5, 6] class = Yes 3346->3354 3348 ASIRETR_4.0 <= 0.5 entropy = 0.258 samples = 23 value = [22, 1] class = No 3347->3348 3353 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3347->3353 3349 entropy = 0.0 samples = 17 value = [17, 0] class = No 3348->3349 3350 HIT1A_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3348->3350 3351 entropy = 0.0 samples = 5 value = [5, 0] class = No 3350->3351 3352 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3350->3352 3355 entropy = 0.0 samples = 2 value = [2, 0] class = No 3354->3355 3356 FLUVACYR_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 3354->3356 3357 AHSTATYR_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [1, 6] class = Yes 3356->3357 3360 entropy = 0.0 samples = 2 value = [2, 0] class = No 3356->3360 3358 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 3357->3358 3359 entropy = 0.0 samples = 1 value = [1, 0] class = No 3357->3359 3362 CHPAIN6M_4.0 <= 0.5 entropy = 0.84 samples = 52 value = [38, 14] class = No 3361->3362 3391 HIT1A_2.0 <= 0.5 entropy = 0.94 samples = 14 value = [5, 9] class = Yes 3361->3391 3363 DIBREL_2.0 <= 0.5 entropy = 0.795 samples = 50 value = [38, 12] class = No 3362->3363 3390 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3362->3390 3364 entropy = 0.0 samples = 7 value = [7, 0] class = No 3363->3364 3365 ASICNHC_2.0 <= 0.5 entropy = 0.854 samples = 43 value = [31, 12] class = No 3363->3365 3366 PAINLB_2.0 <= 0.5 entropy = 0.9 samples = 38 value = [26, 12] class = No 3365->3366 3389 entropy = 0.0 samples = 5 value = [5, 0] class = No 3365->3389 3367 BMI <= 2121.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 3366->3367 3376 AHCNOYR2 <= 7.5 entropy = 0.779 samples = 26 value = [20, 6] class = No 3366->3376 3368 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3367->3368 3369 YRSWRKPA <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 3367->3369 3370 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3369->3370 3371 ASIMEDC_4.0 <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 3369->3371 3372 entropy = 0.0 samples = 5 value = [5, 0] class = No 3371->3372 3373 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3371->3373 3374 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3373->3374 3375 entropy = 0.0 samples = 1 value = [1, 0] class = No 3373->3375 3377 BMI <= 2101.5 entropy = 0.954 samples = 16 value = [10, 6] class = No 3376->3377 3388 entropy = 0.0 samples = 10 value = [10, 0] class = No 3376->3388 3378 entropy = 0.0 samples = 4 value = [4, 0] class = No 3377->3378 3379 BEDDAYR <= 0.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 3377->3379 3380 AHCNOYR2 <= 6.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 3379->3380 3383 VIMGLASS_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 3379->3383 3381 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3380->3381 3382 entropy = 0.0 samples = 1 value = [1, 0] class = No 3380->3382 3384 BEDDAYR <= 28.0 entropy = 0.65 samples = 6 value = [5, 1] class = No 3383->3384 3387 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3383->3387 3385 entropy = 0.0 samples = 5 value = [5, 0] class = No 3384->3385 3386 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3384->3386 3392 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 3391->3392 3393 SMKSTAT2_3.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3391->3393 3394 entropy = 0.0 samples = 5 value = [5, 0] class = No 3393->3394 3395 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3393->3395 3397 DBHVCLN_2.0 <= 0.5 entropy = 0.85 samples = 442 value = [320, 122] class = No 3396->3397 3614 BEDDAYR <= 3.5 entropy = 0.692 samples = 383 value = [312, 71] class = No 3396->3614 3398 BMI <= 2367.0 entropy = 0.793 samples = 297 value = [226, 71] class = No 3397->3398 3535 ASIRETR_2.0 <= 0.5 entropy = 0.936 samples = 145 value = [94, 51] class = No 3397->3535 3399 BMI <= 2320.5 entropy = 0.433 samples = 90 value = [82, 8] class = No 3398->3399 3426 HIT1A_2.0 <= 0.5 entropy = 0.887 samples = 207 value = [144, 63] class = No 3398->3426 3400 BMI <= 2290.5 entropy = 0.513 samples = 70 value = [62, 8] class = No 3399->3400 3425 entropy = 0.0 samples = 20 value = [20, 0] class = No 3399->3425 3401 AHCNOYR2 <= 5.5 entropy = 0.367 samples = 57 value = [53, 4] class = No 3400->3401 3418 ASIRETR_4.0 <= 0.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 3400->3418 3402 DIBREL_2.0 <= 0.5 entropy = 0.235 samples = 52 value = [50, 2] class = No 3401->3402 3411 YRSWRKPA <= 21.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 3401->3411 3403 BMI <= 2092.0 entropy = 0.592 samples = 14 value = [12, 2] class = No 3402->3403 3410 entropy = 0.0 samples = 38 value = [38, 0] class = No 3402->3410 3404 VIMGLASS_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 3403->3404 3409 entropy = 0.0 samples = 7 value = [7, 0] class = No 3403->3409 3405 BMI <= 2074.0 entropy = 0.65 samples = 6 value = [5, 1] class = No 3404->3405 3408 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3404->3408 3406 entropy = 0.0 samples = 5 value = [5, 0] class = No 3405->3406 3407 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3405->3407 3412 entropy = 0.0 samples = 2 value = [2, 0] class = No 3411->3412 3413 ARTH1_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3411->3413 3414 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3413->3414 3415 ASIMEDC_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3413->3415 3416 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3415->3416 3417 entropy = 0.0 samples = 1 value = [1, 0] class = No 3415->3417 3419 BEDDAYR <= 1.0 entropy = 0.991 samples = 9 value = [5, 4] class = No 3418->3419 3424 entropy = 0.0 samples = 4 value = [4, 0] class = No 3418->3424 3420 AHCNOYR2 <= 3.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 3419->3420 3423 entropy = 0.0 samples = 3 value = [3, 0] class = No 3419->3423 3421 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3420->3421 3422 entropy = 0.0 samples = 2 value = [2, 0] class = No 3420->3422 3427 BMI <= 2584.5 entropy = 0.952 samples = 140 value = [88, 52] class = No 3426->3427 3506 JNTSYMP_2.0 <= 0.5 entropy = 0.644 samples = 67 value = [56, 11] class = No 3426->3506 3428 R_MARITL_4 <= 0.5 entropy = 0.742 samples = 57 value = [45, 12] class = No 3427->3428 3461 BMI <= 2611.0 entropy = 0.999 samples = 83 value = [43, 40] class = No 3427->3461 3429 ASISTLV_2.0 <= 0.5 entropy = 0.599 samples = 48 value = [41, 7] class = No 3428->3429 3454 ASIRETR_4.0 <= 0.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 3428->3454 3430 BMI <= 2509.5 entropy = 0.689 samples = 38 value = [31, 7] class = No 3429->3430 3453 entropy = 0.0 samples = 10 value = [10, 0] class = No 3429->3453 3431 YRSWRKPA <= 32.5 entropy = 0.797 samples = 29 value = [22, 7] class = No 3430->3431 3452 entropy = 0.0 samples = 9 value = [9, 0] class = No 3430->3452 3432 PDSICKA_2.0 <= 0.5 entropy = 0.75 samples = 28 value = [22, 6] class = No 3431->3432 3451 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3431->3451 3433 ASIMEDC_2.0 <= 0.5 entropy = 0.845 samples = 22 value = [16, 6] class = No 3432->3433 3450 entropy = 0.0 samples = 6 value = [6, 0] class = No 3432->3450 3434 AHCNOYR2 <= 1.5 entropy = 0.672 samples = 17 value = [14, 3] class = No 3433->3434 3445 ASICNHC_4.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 3433->3445 3435 ARTH1_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3434->3435 3440 AHCNOYR2 <= 4.0 entropy = 0.371 samples = 14 value = [13, 1] class = No 3434->3440 3436 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3435->3436 3437 YRSWRKPA <= 15.0 entropy = 1.0 samples = 2 value = [1, 1] class = No 3435->3437 3438 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3437->3438 3439 entropy = 0.0 samples = 1 value = [1, 0] class = No 3437->3439 3441 entropy = 0.0 samples = 12 value = [12, 0] class = No 3440->3441 3442 ASISTLV_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3440->3442 3443 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3442->3443 3444 entropy = 0.0 samples = 1 value = [1, 0] class = No 3442->3444 3446 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3445->3446 3447 YRSWRKPA <= 26.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3445->3447 3448 entropy = 0.0 samples = 2 value = [2, 0] class = No 3447->3448 3449 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3447->3449 3455 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3454->3455 3456 BMI <= 2449.0 entropy = 0.722 samples = 5 value = [4, 1] class = No 3454->3456 3457 JNTSYMP_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3456->3457 3460 entropy = 0.0 samples = 3 value = [3, 0] class = No 3456->3460 3458 entropy = 0.0 samples = 1 value = [1, 0] class = No 3457->3458 3459 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3457->3459 3462 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3461->3462 3463 ASISTLV_2.0 <= 0.5 entropy = 0.994 samples = 79 value = [43, 36] class = No 3461->3463 3464 ASIMEDC_2.0 <= 0.5 entropy = 0.999 samples = 64 value = [31, 33] class = Yes 3463->3464 3499 JNTSYMP_2.0 <= 0.5 entropy = 0.722 samples = 15 value = [12, 3] class = No 3463->3499 3465 R_MARITL_4 <= 0.5 entropy = 0.999 samples = 60 value = [31, 29] class = No 3464->3465 3498 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3464->3498 3466 BMI <= 2977.0 entropy = 0.999 samples = 56 value = [27, 29] class = Yes 3465->3466 3497 entropy = 0.0 samples = 4 value = [4, 0] class = No 3465->3497 3467 WRKLYR4_2.0 <= 0.5 entropy = 0.994 samples = 44 value = [24, 20] class = No 3466->3467 3490 ASIMEDC_4.0 <= 0.5 entropy = 0.811 samples = 12 value = [3, 9] class = Yes 3466->3490 3468 BMI <= 2726.0 entropy = 0.994 samples = 33 value = [15, 18] class = Yes 3467->3468 3485 BMI <= 2742.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 3467->3485 3469 BEDDAYR <= 2.5 entropy = 0.469 samples = 10 value = [1, 9] class = Yes 3468->3469 3472 DIBREL_2.0 <= 0.5 entropy = 0.966 samples = 23 value = [14, 9] class = No 3468->3472 3470 entropy = 0.0 samples = 9 value = [0, 9] class = Yes 3469->3470 3471 entropy = 0.0 samples = 1 value = [1, 0] class = No 3469->3471 3473 ASISTLV_4.0 <= 0.5 entropy = 0.845 samples = 11 value = [3, 8] class = Yes 3472->3473 3480 PDSICKA_2.0 <= 0.5 entropy = 0.414 samples = 12 value = [11, 1] class = No 3472->3480 3474 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 3473->3474 3475 BMI <= 2925.0 entropy = 0.971 samples = 5 value = [3, 2] class = No 3473->3475 3476 YRSWRKPA <= 26.0 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3475->3476 3479 entropy = 0.0 samples = 2 value = [2, 0] class = No 3475->3479 3477 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3476->3477 3478 entropy = 0.0 samples = 1 value = [1, 0] class = No 3476->3478 3481 entropy = 0.0 samples = 10 value = [10, 0] class = No 3480->3481 3482 HYPEV_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3480->3482 3483 entropy = 0.0 samples = 1 value = [1, 0] class = No 3482->3483 3484 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3482->3484 3486 entropy = 0.0 samples = 7 value = [7, 0] class = No 3485->3486 3487 BMI <= 2824.0 entropy = 1.0 samples = 4 value = [2, 2] class = No 3485->3487 3488 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3487->3488 3489 entropy = 0.0 samples = 2 value = [2, 0] class = No 3487->3489 3491 YRSWRKPA <= 14.0 entropy = 1.0 samples = 6 value = [3, 3] class = No 3490->3491 3496 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 3490->3496 3492 entropy = 0.0 samples = 2 value = [2, 0] class = No 3491->3492 3493 HYBPLEV_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3491->3493 3494 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3493->3494 3495 entropy = 0.0 samples = 1 value = [1, 0] class = No 3493->3495 3500 BEDDAYR <= 1.0 entropy = 1.0 samples = 6 value = [3, 3] class = No 3499->3500 3505 entropy = 0.0 samples = 9 value = [9, 0] class = No 3499->3505 3501 AHCNOYR2 <= 1.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 3500->3501 3504 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3500->3504 3502 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3501->3502 3503 entropy = 0.0 samples = 3 value = [3, 0] class = No 3501->3503 3507 PAINLB_2.0 <= 0.5 entropy = 0.937 samples = 17 value = [11, 6] class = No 3506->3507 3518 AHCNOYR2 <= 2.5 entropy = 0.469 samples = 50 value = [45, 5] class = No 3506->3518 3508 entropy = 0.0 samples = 5 value = [5, 0] class = No 3507->3508 3509 BMI <= 2711.0 entropy = 1.0 samples = 12 value = [6, 6] class = No 3507->3509 3510 YRSWRKPA <= 25.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 3509->3510 3515 YRSWRKPA <= 23.0 entropy = 0.722 samples = 5 value = [4, 1] class = No 3509->3515 3511 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3510->3511 3512 AHCNOYR2 <= 7.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 3510->3512 3513 entropy = 0.0 samples = 2 value = [2, 0] class = No 3512->3513 3514 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3512->3514 3516 entropy = 0.0 samples = 4 value = [4, 0] class = No 3515->3516 3517 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3515->3517 3519 BEDDAYR <= 3.0 entropy = 0.592 samples = 35 value = [30, 5] class = No 3518->3519 3534 entropy = 0.0 samples = 15 value = [15, 0] class = No 3518->3534 3520 DBHVWLY_2.0 <= 0.5 entropy = 0.523 samples = 34 value = [30, 4] class = No 3519->3520 3533 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3519->3533 3521 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3520->3521 3522 ASICNHC_4.0 <= 0.5 entropy = 0.439 samples = 33 value = [30, 3] class = No 3520->3522 3523 HYBPLEV_2.0 <= 0.5 entropy = 0.811 samples = 12 value = [9, 3] class = No 3522->3523 3532 entropy = 0.0 samples = 21 value = [21, 0] class = No 3522->3532 3524 YRSWRKPA <= 33.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 3523->3524 3531 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3523->3531 3525 YRSWRKPA <= 15.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 3524->3525 3530 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3524->3530 3526 HYPEV_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3525->3526 3529 entropy = 0.0 samples = 8 value = [8, 0] class = No 3525->3529 3527 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3526->3527 3528 entropy = 0.0 samples = 1 value = [1, 0] class = No 3526->3528 3536 BMI <= 1944.0 entropy = 0.879 samples = 114 value = [80, 34] class = No 3535->3536 3595 BMI <= 2625.0 entropy = 0.993 samples = 31 value = [14, 17] class = Yes 3535->3595 3537 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3536->3537 3538 HIT1A_2.0 <= 0.5 entropy = 0.863 samples = 112 value = [80, 32] class = No 3536->3538 3539 ASIMEDC_4.0 <= 0.5 entropy = 0.752 samples = 65 value = [51, 14] class = No 3538->3539 3568 BMI <= 2859.0 entropy = 0.96 samples = 47 value = [29, 18] class = No 3538->3568 3540 YRSWRKPA <= 10.5 entropy = 0.909 samples = 37 value = [25, 12] class = No 3539->3540 3561 BMI <= 3026.0 entropy = 0.371 samples = 28 value = [26, 2] class = No 3539->3561 3541 entropy = 0.0 samples = 4 value = [4, 0] class = No 3540->3541 3542 DOINGLWA_5.0 <= 0.5 entropy = 0.946 samples = 33 value = [21, 12] class = No 3540->3542 3543 PAINLB_2.0 <= 0.5 entropy = 0.994 samples = 22 value = [12, 10] class = No 3542->3543 3556 PAINLB_2.0 <= 0.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 3542->3556 3544 YRSWRKPA <= 28.0 entropy = 0.592 samples = 7 value = [6, 1] class = No 3543->3544 3547 DIBREL_2.0 <= 0.5 entropy = 0.971 samples = 15 value = [6, 9] class = Yes 3543->3547 3545 entropy = 0.0 samples = 6 value = [6, 0] class = No 3544->3545 3546 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3544->3546 3548 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3547->3548 3549 BEDDAYR <= 1.5 entropy = 0.994 samples = 11 value = [6, 5] class = No 3547->3549 3550 BMI <= 2463.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 3549->3550 3555 entropy = 0.0 samples = 3 value = [3, 0] class = No 3549->3555 3551 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3550->3551 3552 R_MARITL_4 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 3550->3552 3553 entropy = 0.0 samples = 3 value = [3, 0] class = No 3552->3553 3554 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3552->3554 3557 HYPEV_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 3556->3557 3560 entropy = 0.0 samples = 7 value = [7, 0] class = No 3556->3560 3558 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3557->3558 3559 entropy = 0.0 samples = 2 value = [2, 0] class = No 3557->3559 3562 ASISTLV_4.0 <= 0.5 entropy = 0.229 samples = 27 value = [26, 1] class = No 3561->3562 3567 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3561->3567 3563 YRSWRKPA <= 15.0 entropy = 0.722 samples = 5 value = [4, 1] class = No 3562->3563 3566 entropy = 0.0 samples = 22 value = [22, 0] class = No 3562->3566 3564 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3563->3564 3565 entropy = 0.0 samples = 4 value = [4, 0] class = No 3563->3565 3569 BMI <= 2743.5 entropy = 0.981 samples = 43 value = [25, 18] class = No 3568->3569 3594 entropy = 0.0 samples = 4 value = [4, 0] class = No 3568->3594 3570 BMI <= 2391.0 entropy = 0.935 samples = 37 value = [24, 13] class = No 3569->3570 3591 AHCNOYR2 <= 1.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 3569->3591 3571 AHEARST1_4.0 <= 0.5 entropy = 0.998 samples = 21 value = [10, 11] class = Yes 3570->3571 3586 ASISTLV_2.0 <= 0.5 entropy = 0.544 samples = 16 value = [14, 2] class = No 3570->3586 3572 DIBREL_2.0 <= 0.5 entropy = 0.998 samples = 19 value = [10, 9] class = No 3571->3572 3585 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3571->3585 3573 ASISTLV_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3572->3573 3576 ASISTLV_2.0 <= 0.5 entropy = 0.961 samples = 13 value = [5, 8] class = Yes 3572->3576 3574 entropy = 0.0 samples = 5 value = [5, 0] class = No 3573->3574 3575 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3573->3575 3577 YRSWRKPA <= 30.0 entropy = 0.845 samples = 11 value = [3, 8] class = Yes 3576->3577 3584 entropy = 0.0 samples = 2 value = [2, 0] class = No 3576->3584 3578 YRSWRKPA <= 23.5 entropy = 0.985 samples = 7 value = [3, 4] class = Yes 3577->3578 3583 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3577->3583 3579 AHCNOYR2 <= 2.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 3578->3579 3582 entropy = 0.0 samples = 2 value = [2, 0] class = No 3578->3582 3580 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3579->3580 3581 entropy = 0.0 samples = 1 value = [1, 0] class = No 3579->3581 3587 YRSWRKPA <= 12.5 entropy = 0.353 samples = 15 value = [14, 1] class = No 3586->3587 3590 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3586->3590 3588 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3587->3588 3589 entropy = 0.0 samples = 14 value = [14, 0] class = No 3587->3589 3592 entropy = 0.0 samples = 1 value = [1, 0] class = No 3591->3592 3593 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 3591->3593 3596 BMI <= 2501.5 entropy = 0.863 samples = 21 value = [6, 15] class = Yes 3595->3596 3609 DIBREL_2.0 <= 0.5 entropy = 0.722 samples = 10 value = [8, 2] class = No 3595->3609 3597 BEDDAYR <= 1.5 entropy = 0.937 samples = 17 value = [6, 11] class = Yes 3596->3597 3608 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3596->3608 3598 BMI <= 2345.0 entropy = 0.985 samples = 14 value = [6, 8] class = Yes 3597->3598 3607 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3597->3607 3599 YRSWRKPA <= 19.0 entropy = 0.845 samples = 11 value = [3, 8] class = Yes 3598->3599 3606 entropy = 0.0 samples = 3 value = [3, 0] class = No 3598->3606 3600 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 3599->3600 3601 BEDDAYR <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3599->3601 3602 ASISTLV_4.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 3601->3602 3605 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3601->3605 3603 entropy = 0.0 samples = 3 value = [3, 0] class = No 3602->3603 3604 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3602->3604 3610 AHCNOYR2 <= 3.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3609->3610 3613 entropy = 0.0 samples = 7 value = [7, 0] class = No 3609->3613 3611 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3610->3611 3612 entropy = 0.0 samples = 1 value = [1, 0] class = No 3610->3612 3615 AHCNOYR2 <= 6.5 entropy = 0.652 samples = 358 value = [298, 60] class = No 3614->3615 3748 DOINGLWA_5.0 <= 0.5 entropy = 0.99 samples = 25 value = [14, 11] class = No 3614->3748 3616 ASIRETR_4.0 <= 0.5 entropy = 0.621 samples = 343 value = [290, 53] class = No 3615->3616 3739 SMKSTAT2_3.0 <= 0.5 entropy = 0.997 samples = 15 value = [8, 7] class = No 3615->3739 3617 BMI <= 2284.5 entropy = 0.696 samples = 224 value = [182, 42] class = No 3616->3617 3710 HYPEV_2.0 <= 0.5 entropy = 0.445 samples = 119 value = [108, 11] class = No 3616->3710 3618 PAINLB_2.0 <= 0.5 entropy = 0.391 samples = 52 value = [48, 4] class = No 3617->3618 3631 AHSTATYR_2.0 <= 0.5 entropy = 0.762 samples = 172 value = [134, 38] class = No 3617->3631 3619 ASISTLV_4.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 3618->3619 3624 HYPEV_2.0 <= 0.5 entropy = 0.156 samples = 44 value = [43, 1] class = No 3618->3624 3620 CHLEV_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3619->3620 3623 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3619->3623 3621 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3620->3621 3622 entropy = 0.0 samples = 5 value = [5, 0] class = No 3620->3622 3625 AHCNOYR2 <= 2.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 3624->3625 3630 entropy = 0.0 samples = 34 value = [34, 0] class = No 3624->3630 3626 entropy = 0.0 samples = 7 value = [7, 0] class = No 3625->3626 3627 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3625->3627 3628 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3627->3628 3629 entropy = 0.0 samples = 2 value = [2, 0] class = No 3627->3629 3632 PAINLB_2.0 <= 0.5 entropy = 0.738 samples = 168 value = [133, 35] class = No 3631->3632 3707 CHPAIN6M_4.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3631->3707 3633 DBHVWLY_2.0 <= 0.5 entropy = 0.469 samples = 30 value = [27, 3] class = No 3632->3633 3642 HYBPLEV_2.0 <= 0.5 entropy = 0.781 samples = 138 value = [106, 32] class = No 3632->3642 3634 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3633->3634 3635 AHCNOYR2 <= 0.5 entropy = 0.362 samples = 29 value = [27, 2] class = No 3633->3635 3636 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3635->3636 3637 AHCNOYR2 <= 5.5 entropy = 0.222 samples = 28 value = [27, 1] class = No 3635->3637 3638 entropy = 0.0 samples = 26 value = [26, 0] class = No 3637->3638 3639 YRSWRKPA <= 13.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3637->3639 3640 entropy = 0.0 samples = 1 value = [1, 0] class = No 3639->3640 3641 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3639->3641 3643 DBHVCLN_2.0 <= 0.5 entropy = 0.743 samples = 128 value = [101, 27] class = No 3642->3643 3702 YRSWRKPA <= 28.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 3642->3702 3644 PDSICKA_2.0 <= 0.5 entropy = 0.61 samples = 80 value = [68, 12] class = No 3643->3644 3673 BEDDAYR <= 0.5 entropy = 0.896 samples = 48 value = [33, 15] class = No 3643->3673 3645 DIBREL_2.0 <= 0.5 entropy = 0.736 samples = 58 value = [46, 12] class = No 3644->3645 3672 entropy = 0.0 samples = 22 value = [22, 0] class = No 3644->3672 3646 BMI <= 3076.5 entropy = 0.931 samples = 26 value = [17, 9] class = No 3645->3646 3661 HIT1A_2.0 <= 0.5 entropy = 0.449 samples = 32 value = [29, 3] class = No 3645->3661 3647 ASISTLV_4.0 <= 0.5 entropy = 0.871 samples = 24 value = [17, 7] class = No 3646->3647 3660 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3646->3660 3648 BMI <= 2314.0 entropy = 0.544 samples = 16 value = [14, 2] class = No 3647->3648 3655 YRSWRKPA <= 22.0 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 3647->3655 3649 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3648->3649 3650 YRSWRKPA <= 10.5 entropy = 0.353 samples = 15 value = [14, 1] class = No 3648->3650 3651 CHLEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3650->3651 3654 entropy = 0.0 samples = 12 value = [12, 0] class = No 3650->3654 3652 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3651->3652 3653 entropy = 0.0 samples = 2 value = [2, 0] class = No 3651->3653 3656 ASIMEDC_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 3655->3656 3659 entropy = 0.0 samples = 2 value = [2, 0] class = No 3655->3659 3657 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 3656->3657 3658 entropy = 0.0 samples = 1 value = [1, 0] class = No 3656->3658 3662 entropy = 0.0 samples = 20 value = [20, 0] class = No 3661->3662 3663 VIMGLASS_2.0 <= 0.5 entropy = 0.811 samples = 12 value = [9, 3] class = No 3661->3663 3664 AHCNOYR2 <= 1.5 entropy = 0.503 samples = 9 value = [8, 1] class = No 3663->3664 3669 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3663->3669 3665 SMKSTAT2_3.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3664->3665 3668 entropy = 0.0 samples = 7 value = [7, 0] class = No 3664->3668 3666 entropy = 0.0 samples = 1 value = [1, 0] class = No 3665->3666 3667 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3665->3667 3670 entropy = 0.0 samples = 1 value = [1, 0] class = No 3669->3670 3671 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3669->3671 3674 BMI <= 3137.0 entropy = 0.967 samples = 33 value = [20, 13] class = No 3673->3674 3697 BMI <= 2797.5 entropy = 0.567 samples = 15 value = [13, 2] class = No 3673->3697 3675 AHCNOYR2 <= 2.5 entropy = 0.987 samples = 30 value = [17, 13] class = No 3674->3675 3696 entropy = 0.0 samples = 3 value = [3, 0] class = No 3674->3696 3676 YRSWRKPA <= 22.5 entropy = 0.999 samples = 23 value = [11, 12] class = Yes 3675->3676 3691 YRSWRKPA <= 19.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 3675->3691 3677 SMKSTAT2_3.0 <= 0.5 entropy = 0.982 samples = 19 value = [11, 8] class = No 3676->3677 3690 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3676->3690 3678 YRSWRKPA <= 12.5 entropy = 0.997 samples = 15 value = [7, 8] class = Yes 3677->3678 3689 entropy = 0.0 samples = 4 value = [4, 0] class = No 3677->3689 3679 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 3678->3679 3680 AHCNOYR2 <= 0.5 entropy = 0.881 samples = 10 value = [7, 3] class = No 3678->3680 3681 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3680->3681 3682 ASIMEDC_4.0 <= 0.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 3680->3682 3683 R_MARITL_4 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 3682->3683 3688 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3682->3688 3684 entropy = 0.0 samples = 6 value = [6, 0] class = No 3683->3684 3685 ASISTLV_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3683->3685 3686 entropy = 0.0 samples = 1 value = [1, 0] class = No 3685->3686 3687 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3685->3687 3692 ASISTLV_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3691->3692 3695 entropy = 0.0 samples = 5 value = [5, 0] class = No 3691->3695 3693 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3692->3693 3694 entropy = 0.0 samples = 1 value = [1, 0] class = No 3692->3694 3698 entropy = 0.0 samples = 10 value = [10, 0] class = No 3697->3698 3699 YRSWRKPA <= 13.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 3697->3699 3700 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3699->3700 3701 entropy = 0.0 samples = 3 value = [3, 0] class = No 3699->3701 3703 BMI <= 2609.0 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 3702->3703 3706 entropy = 0.0 samples = 3 value = [3, 0] class = No 3702->3706 3704 entropy = 0.0 samples = 2 value = [2, 0] class = No 3703->3704 3705 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 3703->3705 3708 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3707->3708 3709 entropy = 0.0 samples = 1 value = [1, 0] class = No 3707->3709 3711 SMKSTAT2_3.0 <= 0.5 entropy = 0.722 samples = 40 value = [32, 8] class = No 3710->3711 3732 BEDDAYR <= 1.5 entropy = 0.233 samples = 79 value = [76, 3] class = No 3710->3732 3712 AHEARST1_4.0 <= 0.5 entropy = 0.887 samples = 23 value = [16, 7] class = No 3711->3712 3727 R_MARITL_4 <= 0.5 entropy = 0.323 samples = 17 value = [16, 1] class = No 3711->3727 3713 DBHVCLN_2.0 <= 0.5 entropy = 0.792 samples = 21 value = [16, 5] class = No 3712->3713 3726 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3712->3726 3714 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 15 value = [10, 5] class = No 3713->3714 3725 entropy = 0.0 samples = 6 value = [6, 0] class = No 3713->3725 3715 entropy = 0.0 samples = 4 value = [4, 0] class = No 3714->3715 3716 HYBPLEV_2.0 <= 0.5 entropy = 0.994 samples = 11 value = [6, 5] class = No 3714->3716 3717 BMI <= 2963.5 entropy = 0.991 samples = 9 value = [4, 5] class = Yes 3716->3717 3724 entropy = 0.0 samples = 2 value = [2, 0] class = No 3716->3724 3718 YRSWRKPA <= 34.0 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 3717->3718 3723 entropy = 0.0 samples = 2 value = [2, 0] class = No 3717->3723 3719 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3718->3719 3720 HIT1A_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3718->3720 3721 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3720->3721 3722 entropy = 0.0 samples = 2 value = [2, 0] class = No 3720->3722 3728 entropy = 0.0 samples = 15 value = [15, 0] class = No 3727->3728 3729 BMI <= 2538.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3727->3729 3730 entropy = 0.0 samples = 1 value = [1, 0] class = No 3729->3730 3731 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3729->3731 3733 entropy = 0.0 samples = 68 value = [68, 0] class = No 3732->3733 3734 ARTH1_2.0 <= 0.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 3732->3734 3735 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3734->3735 3736 YRSWRKPA <= 11.0 entropy = 0.503 samples = 9 value = [8, 1] class = No 3734->3736 3737 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3736->3737 3738 entropy = 0.0 samples = 8 value = [8, 0] class = No 3736->3738 3740 HIT1A_2.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 3739->3740 3747 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3739->3747 3741 WRKLYR4_2.0 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 3740->3741 3744 BMI <= 2641.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3740->3744 3742 entropy = 0.0 samples = 7 value = [7, 0] class = No 3741->3742 3743 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3741->3743 3745 entropy = 0.0 samples = 1 value = [1, 0] class = No 3744->3745 3746 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3744->3746 3749 YRSWRKPA <= 15.5 entropy = 0.946 samples = 22 value = [14, 8] class = No 3748->3749 3762 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3748->3762 3750 DBHVCLN_2.0 <= 0.5 entropy = 0.98 samples = 12 value = [5, 7] class = Yes 3749->3750 3759 YRSWRKPA <= 32.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 3749->3759 3751 AHSTATYR_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 3750->3751 3758 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 3750->3758 3752 HIT1A_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3751->3752 3757 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3751->3757 3753 entropy = 0.0 samples = 4 value = [4, 0] class = No 3752->3753 3754 ASIMEDC_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3752->3754 3755 entropy = 0.0 samples = 1 value = [1, 0] class = No 3754->3755 3756 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3754->3756 3760 entropy = 0.0 samples = 9 value = [9, 0] class = No 3759->3760 3761 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3759->3761 3764 BMI <= 4007.0 entropy = 0.967 samples = 193 value = [117, 76] class = No 3763->3764 3879 HYBPLEV_2.0 <= 0.5 entropy = 0.74 samples = 86 value = [68, 18] class = No 3763->3879 3765 AHSTATYR_2.0 <= 0.5 entropy = 0.953 samples = 185 value = [116, 69] class = No 3764->3765 3874 R_MARITL_4 <= 0.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 3764->3874 3766 JNTSYMP_2.0 <= 0.5 entropy = 0.963 samples = 178 value = [109, 69] class = No 3765->3766 3873 entropy = 0.0 samples = 7 value = [7, 0] class = No 3765->3873 3767 YRSWRKPA <= 16.5 entropy = 0.987 samples = 37 value = [16, 21] class = Yes 3766->3767 3790 HYBPLEV_2.0 <= 0.5 entropy = 0.925 samples = 141 value = [93, 48] class = No 3766->3790 3768 AHCNOYR2 <= 1.5 entropy = 0.894 samples = 29 value = [9, 20] class = Yes 3767->3768 3785 CHPAIN6M_3.0 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 3767->3785 3769 FLUVACYR_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 3768->3769 3776 FLUVACYR_2.0 <= 0.5 entropy = 0.684 samples = 22 value = [4, 18] class = Yes 3768->3776 3770 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3769->3770 3771 ASICNHC_4.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3769->3771 3772 entropy = 0.0 samples = 4 value = [4, 0] class = No 3771->3772 3773 DIBREL_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3771->3773 3774 entropy = 0.0 samples = 1 value = [1, 0] class = No 3773->3774 3775 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3773->3775 3777 BMI <= 3291.5 entropy = 0.971 samples = 10 value = [4, 6] class = Yes 3776->3777 3784 entropy = 0.0 samples = 12 value = [0, 12] class = Yes 3776->3784 3778 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3777->3778 3779 BEDDAYR <= 1.0 entropy = 0.918 samples = 6 value = [4, 2] class = No 3777->3779 3780 entropy = 0.0 samples = 3 value = [3, 0] class = No 3779->3780 3781 ASIMEDC_4.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3779->3781 3782 entropy = 0.0 samples = 1 value = [1, 0] class = No 3781->3782 3783 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3781->3783 3786 entropy = 0.0 samples = 6 value = [6, 0] class = No 3785->3786 3787 ASIRETR_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3785->3787 3788 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3787->3788 3789 entropy = 0.0 samples = 1 value = [1, 0] class = No 3787->3789 3791 YRSWRKPA <= 0.5 entropy = 0.943 samples = 133 value = [85, 48] class = No 3790->3791 3872 entropy = 0.0 samples = 8 value = [8, 0] class = No 3790->3872 3792 DBHVWLY_2.0 <= 0.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 3791->3792 3795 CHPAIN6M_3.0 <= 0.5 entropy = 0.962 samples = 122 value = [75, 47] class = No 3791->3795 3793 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3792->3793 3794 entropy = 0.0 samples = 10 value = [10, 0] class = No 3792->3794 3796 YRSWRKPA <= 3.5 entropy = 0.954 samples = 120 value = [75, 45] class = No 3795->3796 3871 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3795->3871 3797 AHCNOYR2 <= 4.0 entropy = 1.0 samples = 34 value = [17, 17] class = No 3796->3797 3822 DIBPRE2_2.0 <= 0.5 entropy = 0.91 samples = 86 value = [58, 28] class = No 3796->3822 3798 BMI <= 3825.5 entropy = 0.993 samples = 31 value = [17, 14] class = No 3797->3798 3821 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3797->3821 3799 DIBPRE2_2.0 <= 0.5 entropy = 1.0 samples = 28 value = [14, 14] class = No 3798->3799 3820 entropy = 0.0 samples = 3 value = [3, 0] class = No 3798->3820 3800 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3799->3800 3801 ASIRETR_4.0 <= 0.5 entropy = 0.99 samples = 25 value = [14, 11] class = No 3799->3801 3802 BMI <= 3215.0 entropy = 0.991 samples = 18 value = [8, 10] class = Yes 3801->3802 3815 FLUVACYR_2.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 3801->3815 3803 entropy = 0.0 samples = 2 value = [2, 0] class = No 3802->3803 3804 DIBREL_2.0 <= 0.5 entropy = 0.954 samples = 16 value = [6, 10] class = Yes 3802->3804 3805 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3804->3805 3806 YRSWRKPA <= 1.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 3804->3806 3807 entropy = 0.0 samples = 3 value = [3, 0] class = No 3806->3807 3808 BMI <= 3700.5 entropy = 0.918 samples = 9 value = [3, 6] class = Yes 3806->3808 3809 BEDDAYR <= 1.0 entropy = 1.0 samples = 6 value = [3, 3] class = No 3808->3809 3814 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3808->3814 3810 entropy = 0.0 samples = 2 value = [2, 0] class = No 3809->3810 3811 BEDDAYR <= 4.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3809->3811 3812 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3811->3812 3813 entropy = 0.0 samples = 1 value = [1, 0] class = No 3811->3813 3816 BMI <= 3565.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3815->3816 3819 entropy = 0.0 samples = 4 value = [4, 0] class = No 3815->3819 3817 entropy = 0.0 samples = 2 value = [2, 0] class = No 3816->3817 3818 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3816->3818 3823 entropy = 0.0 samples = 5 value = [5, 0] class = No 3822->3823 3824 YRSWRKPA <= 11.5 entropy = 0.93 samples = 81 value = [53, 28] class = No 3822->3824 3825 BMI <= 3309.0 entropy = 0.779 samples = 39 value = [30, 9] class = No 3824->3825 3846 BMI <= 3315.0 entropy = 0.993 samples = 42 value = [23, 19] class = No 3824->3846 3826 AHCNOYR2 <= 1.5 entropy = 0.989 samples = 16 value = [9, 7] class = No 3825->3826 3841 ASIMEDC_2.0 <= 0.5 entropy = 0.426 samples = 23 value = [21, 2] class = No 3825->3841 3827 entropy = 0.0 samples = 3 value = [3, 0] class = No 3826->3827 3828 ASIMEDC_2.0 <= 0.5 entropy = 0.996 samples = 13 value = [6, 7] class = Yes 3826->3828 3829 BMI <= 3264.5 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 3828->3829 3840 entropy = 0.0 samples = 2 value = [2, 0] class = No 3828->3840 3830 FLUVACYR_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 3829->3830 3835 DBHVCLN_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 3829->3835 3831 BMI <= 3254.0 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3830->3831 3834 entropy = 0.0 samples = 2 value = [2, 0] class = No 3830->3834 3832 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3831->3832 3833 entropy = 0.0 samples = 1 value = [1, 0] class = No 3831->3833 3836 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3835->3836 3837 ASIMEDC_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3835->3837 3838 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3837->3838 3839 entropy = 0.0 samples = 1 value = [1, 0] class = No 3837->3839 3842 entropy = 0.0 samples = 19 value = [19, 0] class = No 3841->3842 3843 R_MARITL_4 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 3841->3843 3844 entropy = 0.0 samples = 2 value = [2, 0] class = No 3843->3844 3845 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3843->3845 3847 YRSWRKPA <= 13.5 entropy = 0.75 samples = 14 value = [11, 3] class = No 3846->3847 3856 BEDDAYR <= 2.5 entropy = 0.985 samples = 28 value = [12, 16] class = Yes 3846->3856 3848 AHCNOYR2 <= 2.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3847->3848 3851 AHCNOYR2 <= 1.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 3847->3851 3849 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3848->3849 3850 entropy = 0.0 samples = 1 value = [1, 0] class = No 3848->3850 3852 ASIRETR_4.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3851->3852 3855 entropy = 0.0 samples = 9 value = [9, 0] class = No 3851->3855 3853 entropy = 0.0 samples = 1 value = [1, 0] class = No 3852->3853 3854 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3852->3854 3857 BMI <= 3353.5 entropy = 0.999 samples = 25 value = [12, 13] class = Yes 3856->3857 3870 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3856->3870 3858 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3857->3858 3859 YRSWRKPA <= 16.5 entropy = 0.994 samples = 22 value = [12, 10] class = No 3857->3859 3860 BMI <= 3432.0 entropy = 0.946 samples = 11 value = [4, 7] class = Yes 3859->3860 3865 ASIRETR_4.0 <= 0.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 3859->3865 3861 entropy = 0.0 samples = 3 value = [3, 0] class = No 3860->3861 3862 YRSWRKPA <= 12.5 entropy = 0.544 samples = 8 value = [1, 7] class = Yes 3860->3862 3863 entropy = 0.0 samples = 1 value = [1, 0] class = No 3862->3863 3864 entropy = 0.0 samples = 7 value = [0, 7] class = Yes 3862->3864 3866 entropy = 0.0 samples = 6 value = [6, 0] class = No 3865->3866 3867 DBHVCLN_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 3865->3867 3868 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3867->3868 3869 entropy = 0.0 samples = 2 value = [2, 0] class = No 3867->3869 3875 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 3874->3875 3876 DBHVCLN_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3874->3876 3877 entropy = 0.0 samples = 1 value = [1, 0] class = No 3876->3877 3878 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3876->3878 3880 AHCNOYR2 <= 7.5 entropy = 0.65 samples = 78 value = [65, 13] class = No 3879->3880 3905 PAINLB_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [3, 5] class = Yes 3879->3905 3881 DBHVWLY_2.0 <= 0.5 entropy = 0.539 samples = 73 value = [64, 9] class = No 3880->3881 3902 BEDDAYR <= 12.0 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 3880->3902 3882 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3881->3882 3883 ASIMEDC_4.0 <= 0.5 entropy = 0.465 samples = 71 value = [64, 7] class = No 3881->3883 3884 ASIRETR_4.0 <= 0.5 entropy = 0.659 samples = 41 value = [34, 7] class = No 3883->3884 3901 entropy = 0.0 samples = 30 value = [30, 0] class = No 3883->3901 3885 ASICNHC_4.0 <= 0.5 entropy = 0.503 samples = 36 value = [32, 4] class = No 3884->3885 3898 HIT1A_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 3884->3898 3886 YRSWRKPA <= 29.0 entropy = 0.222 samples = 28 value = [27, 1] class = No 3885->3886 3891 BMI <= 3943.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 3885->3891 3887 entropy = 0.0 samples = 26 value = [26, 0] class = No 3886->3887 3888 BMI <= 3239.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3886->3888 3889 entropy = 0.0 samples = 1 value = [1, 0] class = No 3888->3889 3890 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3888->3890 3892 AHCNOYR2 <= 3.0 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 3891->3892 3897 entropy = 0.0 samples = 3 value = [3, 0] class = No 3891->3897 3893 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3892->3893 3894 BMI <= 3729.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3892->3894 3895 entropy = 0.0 samples = 2 value = [2, 0] class = No 3894->3895 3896 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3894->3896 3899 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3898->3899 3900 entropy = 0.0 samples = 2 value = [2, 0] class = No 3898->3900 3903 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3902->3903 3904 entropy = 0.0 samples = 1 value = [1, 0] class = No 3902->3904 3906 entropy = 0.0 samples = 3 value = [3, 0] class = No 3905->3906 3907 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 3905->3907 3909 YRSWRKPA <= 2.5 entropy = 0.151 samples = 505 value = [494, 11] class = No 3908->3909 3956 BMI <= 2828.0 entropy = 0.453 samples = 2371 value = [2146, 225] class = No 3908->3956 3910 JNTSYMP_2.0 <= 0.5 entropy = 0.269 samples = 174 value = [166, 8] class = No 3909->3910 3939 YRSWRKPA <= 9.5 entropy = 0.075 samples = 331 value = [328, 3] class = No 3909->3939 3911 ASICNHC_2.0 <= 0.5 entropy = 0.667 samples = 23 value = [19, 4] class = No 3910->3911 3922 ASISTLV_4.0 <= 0.5 entropy = 0.176 samples = 151 value = [147, 4] class = No 3910->3922 3912 BMI <= 2309.0 entropy = 0.323 samples = 17 value = [16, 1] class = No 3911->3912 3917 ASIMEDC_2.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 3911->3917 3913 CHLEV_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3912->3913 3916 entropy = 0.0 samples = 14 value = [14, 0] class = No 3912->3916 3914 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3913->3914 3915 entropy = 0.0 samples = 2 value = [2, 0] class = No 3913->3915 3918 entropy = 0.0 samples = 2 value = [2, 0] class = No 3917->3918 3919 BMI <= 2302.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3917->3919 3920 entropy = 0.0 samples = 1 value = [1, 0] class = No 3919->3920 3921 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3919->3921 3923 ASIRETR_4.0 <= 0.5 entropy = 0.25 samples = 96 value = [92, 4] class = No 3922->3923 3938 entropy = 0.0 samples = 55 value = [55, 0] class = No 3922->3938 3924 BMI <= 1943.0 entropy = 0.158 samples = 87 value = [85, 2] class = No 3923->3924 3933 PAINLB_2.0 <= 0.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 3923->3933 3925 R_MARITL_4 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3924->3925 3928 BMI <= 3338.0 entropy = 0.093 samples = 84 value = [83, 1] class = No 3924->3928 3926 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3925->3926 3927 entropy = 0.0 samples = 2 value = [2, 0] class = No 3925->3927 3929 entropy = 0.0 samples = 78 value = [78, 0] class = No 3928->3929 3930 BMI <= 3363.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 3928->3930 3931 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3930->3931 3932 entropy = 0.0 samples = 5 value = [5, 0] class = No 3930->3932 3934 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3933->3934 3935 DBHVCLN_2.0 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 3933->3935 3936 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3935->3936 3937 entropy = 0.0 samples = 7 value = [7, 0] class = No 3935->3937 3940 entropy = 0.0 samples = 162 value = [162, 0] class = No 3939->3940 3941 ASIRETR_2.0 <= 0.5 entropy = 0.129 samples = 169 value = [166, 3] class = No 3939->3941 3942 YRSWRKPA <= 10.5 entropy = 0.065 samples = 129 value = [128, 1] class = No 3941->3942 3949 BMI <= 2397.5 entropy = 0.286 samples = 40 value = [38, 2] class = No 3941->3949 3943 FLUVACYR_2.0 <= 0.5 entropy = 0.286 samples = 20 value = [19, 1] class = No 3942->3943 3948 entropy = 0.0 samples = 109 value = [109, 0] class = No 3942->3948 3944 DOINGLWA_5.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3943->3944 3947 entropy = 0.0 samples = 17 value = [17, 0] class = No 3943->3947 3945 entropy = 0.0 samples = 2 value = [2, 0] class = No 3944->3945 3946 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3944->3946 3950 YRSWRKPA <= 17.5 entropy = 0.722 samples = 10 value = [8, 2] class = No 3949->3950 3955 entropy = 0.0 samples = 30 value = [30, 0] class = No 3949->3955 3951 entropy = 0.0 samples = 7 value = [7, 0] class = No 3950->3951 3952 SMKSTAT2_3.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3950->3952 3953 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3952->3953 3954 entropy = 0.0 samples = 1 value = [1, 0] class = No 3952->3954 3957 CHLEV_2.0 <= 0.5 entropy = 0.39 samples = 1827 value = [1687, 140] class = No 3956->3957 4372 VIMGLASS_2.0 <= 0.5 entropy = 0.625 samples = 544 value = [459, 85] class = No 3956->4372 3958 FLUVACYR_2.0 <= 0.5 entropy = 0.538 samples = 301 value = [264, 37] class = No 3957->3958 4053 HYPEV_2.0 <= 0.5 entropy = 0.357 samples = 1526 value = [1423, 103] class = No 3957->4053 3959 BMI <= 2032.5 entropy = 0.657 samples = 171 value = [142, 29] class = No 3958->3959 4024 ARTH1_2.0 <= 0.5 entropy = 0.334 samples = 130 value = [122, 8] class = No 3958->4024 3960 BMI <= 1986.5 entropy = 0.985 samples = 14 value = [8, 6] class = No 3959->3960 3971 ASIMEDC_4.0 <= 0.5 entropy = 0.601 samples = 157 value = [134, 23] class = No 3959->3971 3961 YRSWRKPA <= 24.0 entropy = 0.592 samples = 7 value = [6, 1] class = No 3960->3961 3966 YRSWRKPA <= 11.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 3960->3966 3962 entropy = 0.0 samples = 5 value = [5, 0] class = No 3961->3962 3963 VIMGLASS_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3961->3963 3964 entropy = 0.0 samples = 1 value = [1, 0] class = No 3963->3964 3965 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3963->3965 3967 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 3966->3967 3968 ASIMEDC_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 3966->3968 3969 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3968->3969 3970 entropy = 0.0 samples = 2 value = [2, 0] class = No 3968->3970 3972 YRSWRKPA <= 4.5 entropy = 0.751 samples = 79 value = [62, 17] class = No 3971->3972 4007 BMI <= 2475.5 entropy = 0.391 samples = 78 value = [72, 6] class = No 3971->4007 3973 entropy = 0.0 samples = 13 value = [13, 0] class = No 3972->3973 3974 ASICNHC_4.0 <= 0.5 entropy = 0.823 samples = 66 value = [49, 17] class = No 3972->3974 3975 HIT1A_2.0 <= 0.5 entropy = 0.641 samples = 43 value = [36, 7] class = No 3974->3975 3994 AHCNOYR2 <= 1.5 entropy = 0.988 samples = 23 value = [13, 10] class = No 3974->3994 3976 AHSTATYR_2.0 <= 0.5 entropy = 0.31 samples = 18 value = [17, 1] class = No 3975->3976 3979 ASIMEDC_2.0 <= 0.5 entropy = 0.795 samples = 25 value = [19, 6] class = No 3975->3979 3977 entropy = 0.0 samples = 17 value = [17, 0] class = No 3976->3977 3978 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3976->3978 3980 YRSWRKPA <= 24.0 entropy = 0.94 samples = 14 value = [9, 5] class = No 3979->3980 3989 AMDLONGR_2.0 <= 0.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 3979->3989 3981 YRSWRKPA <= 11.0 entropy = 0.722 samples = 10 value = [8, 2] class = No 3980->3981 3986 YRSWRKPA <= 33.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 3980->3986 3982 BEDDAYR <= 1.0 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 3981->3982 3985 entropy = 0.0 samples = 7 value = [7, 0] class = No 3981->3985 3983 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 3982->3983 3984 entropy = 0.0 samples = 1 value = [1, 0] class = No 3982->3984 3987 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3986->3987 3988 entropy = 0.0 samples = 1 value = [1, 0] class = No 3986->3988 3990 entropy = 0.0 samples = 9 value = [9, 0] class = No 3989->3990 3991 PDSICKA_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 3989->3991 3992 entropy = 0.0 samples = 1 value = [1, 0] class = No 3991->3992 3993 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 3991->3993 3995 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3994->3995 3996 BMI <= 2221.0 entropy = 0.934 samples = 20 value = [13, 7] class = No 3994->3996 3997 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 3996->3997 3998 YRSWRKPA <= 14.0 entropy = 0.787 samples = 17 value = [13, 4] class = No 3996->3998 3999 entropy = 0.0 samples = 6 value = [6, 0] class = No 3998->3999 4000 VIMGLASS_2.0 <= 0.5 entropy = 0.946 samples = 11 value = [7, 4] class = No 3998->4000 4001 SMKSTAT2_3.0 <= 0.5 entropy = 0.764 samples = 9 value = [7, 2] class = No 4000->4001 4006 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4000->4006 4002 entropy = 0.0 samples = 6 value = [6, 0] class = No 4001->4002 4003 HIT1A_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 4001->4003 4004 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4003->4004 4005 entropy = 0.0 samples = 1 value = [1, 0] class = No 4003->4005 4008 ASISTLV_2.0 <= 0.5 entropy = 0.144 samples = 49 value = [48, 1] class = No 4007->4008 4013 AHCNOYR2 <= 2.5 entropy = 0.663 samples = 29 value = [24, 5] class = No 4007->4013 4009 entropy = 0.0 samples = 46 value = [46, 0] class = No 4008->4009 4010 PAINLB_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 4008->4010 4011 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4010->4011 4012 entropy = 0.0 samples = 2 value = [2, 0] class = No 4010->4012 4014 YRSWRKPA <= 1.0 entropy = 0.286 samples = 20 value = [19, 1] class = No 4013->4014 4017 R_MARITL_4 <= 0.5 entropy = 0.991 samples = 9 value = [5, 4] class = No 4013->4017 4015 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4014->4015 4016 entropy = 0.0 samples = 19 value = [19, 0] class = No 4014->4016 4018 SMKSTAT2_3.0 <= 0.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 4017->4018 4023 entropy = 0.0 samples = 3 value = [3, 0] class = No 4017->4023 4019 BEDDAYR <= 5.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 4018->4019 4022 entropy = 0.0 samples = 1 value = [1, 0] class = No 4018->4022 4020 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 4019->4020 4021 entropy = 0.0 samples = 1 value = [1, 0] class = No 4019->4021 4025 entropy = 0.0 samples = 27 value = [27, 0] class = No 4024->4025 4026 AHCNOYR2 <= 2.5 entropy = 0.394 samples = 103 value = [95, 8] class = No 4024->4026 4027 ASICNHC_4.0 <= 0.5 entropy = 0.25 samples = 72 value = [69, 3] class = No 4026->4027 4042 BMI <= 2383.5 entropy = 0.637 samples = 31 value = [26, 5] class = No 4026->4042 4028 entropy = 0.0 samples = 30 value = [30, 0] class = No 4027->4028 4029 YRSWRKPA <= 3.5 entropy = 0.371 samples = 42 value = [39, 3] class = No 4027->4029 4030 entropy = 0.0 samples = 14 value = [14, 0] class = No 4029->4030 4031 YRSWRKPA <= 19.0 entropy = 0.491 samples = 28 value = [25, 3] class = No 4029->4031 4032 YRSWRKPA <= 17.0 entropy = 0.696 samples = 16 value = [13, 3] class = No 4031->4032 4041 entropy = 0.0 samples = 12 value = [12, 0] class = No 4031->4041 4033 AMDLONGR_1.0 <= 0.5 entropy = 0.567 samples = 15 value = [13, 2] class = No 4032->4033 4040 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4032->4040 4034 DBHVCLN_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 4033->4034 4039 entropy = 0.0 samples = 10 value = [10, 0] class = No 4033->4039 4035 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4034->4035 4036 ASIRETR_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 4034->4036 4037 entropy = 0.0 samples = 3 value = [3, 0] class = No 4036->4037 4038 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4036->4038 4043 entropy = 0.0 samples = 13 value = [13, 0] class = No 4042->4043 4044 ASIRETR_4.0 <= 0.5 entropy = 0.852 samples = 18 value = [13, 5] class = No 4042->4044 4045 BMI <= 2544.5 entropy = 0.994 samples = 11 value = [6, 5] class = No 4044->4045 4052 entropy = 0.0 samples = 7 value = [7, 0] class = No 4044->4052 4046 SMKSTAT2_3.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 4045->4046 4049 JNTSYMP_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 4045->4049 4047 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 4046->4047 4048 entropy = 0.0 samples = 1 value = [1, 0] class = No 4046->4048 4050 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4049->4050 4051 entropy = 0.0 samples = 5 value = [5, 0] class = No 4049->4051 4054 YRSWRKPA <= 27.5 entropy = 0.559 samples = 199 value = [173, 26] class = No 4053->4054 4117 VIMGLASS_2.0 <= 0.5 entropy = 0.32 samples = 1327 value = [1250, 77] class = No 4053->4117 4055 DBHVCLN_2.0 <= 0.5 entropy = 0.635 samples = 156 value = [131, 25] class = No 4054->4055 4112 BMI <= 2720.0 entropy = 0.159 samples = 43 value = [42, 1] class = No 4054->4112 4056 BMI <= 2018.5 entropy = 0.902 samples = 22 value = [15, 7] class = No 4055->4056 4069 BMI <= 2089.0 entropy = 0.569 samples = 134 value = [116, 18] class = No 4055->4069 4057 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4056->4057 4058 DIBREL_2.0 <= 0.5 entropy = 0.811 samples = 20 value = [15, 5] class = No 4056->4058 4059 AHCNOYR2 <= 2.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 4058->4059 4064 ASIMEDC_2.0 <= 0.5 entropy = 0.414 samples = 12 value = [11, 1] class = No 4058->4064 4060 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4059->4060 4061 BEDDAYR <= 19.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 4059->4061 4062 entropy = 0.0 samples = 4 value = [4, 0] class = No 4061->4062 4063 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4061->4063 4065 entropy = 0.0 samples = 10 value = [10, 0] class = No 4064->4065 4066 FLUVACYR_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 4064->4066 4067 entropy = 0.0 samples = 1 value = [1, 0] class = No 4066->4067 4068 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4066->4068 4070 entropy = 0.0 samples = 13 value = [13, 0] class = No 4069->4070 4071 CHPAIN6M_4.0 <= 0.5 entropy = 0.607 samples = 121 value = [103, 18] class = No 4069->4071 4072 BMI <= 2101.0 entropy = 0.559 samples = 115 value = [100, 15] class = No 4071->4072 4109 BEDDAYR <= 1.0 entropy = 1.0 samples = 6 value = [3, 3] class = No 4071->4109 4073 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4072->4073 4074 AHCNOYR2 <= 5.5 entropy = 0.537 samples = 114 value = [100, 14] class = No 4072->4074 4075 ASISTLV_4.0 <= 0.5 entropy = 0.463 samples = 102 value = [92, 10] class = No 4074->4075 4104 PDSICKA_2.0 <= 0.5 entropy = 0.918 samples = 12 value = [8, 4] class = No 4074->4104 4076 YRSWRKPA <= 16.0 entropy = 0.604 samples = 61 value = [52, 9] class = No 4075->4076 4099 YRSWRKPA <= 26.0 entropy = 0.165 samples = 41 value = [40, 1] class = No 4075->4099 4077 BMI <= 2787.5 entropy = 0.713 samples = 46 value = [37, 9] class = No 4076->4077 4098 entropy = 0.0 samples = 15 value = [15, 0] class = No 4076->4098 4078 AMDLONGR_1.0 <= 0.5 entropy = 0.675 samples = 45 value = [37, 8] class = No 4077->4078 4097 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4077->4097 4079 ASIRETR_4.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 4078->4079 4084 YRSWRKPA <= 3.5 entropy = 0.552 samples = 39 value = [34, 5] class = No 4078->4084 4080 BMI <= 2638.0 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 4079->4080 4083 entropy = 0.0 samples = 2 value = [2, 0] class = No 4079->4083 4081 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4080->4081 4082 entropy = 0.0 samples = 1 value = [1, 0] class = No 4080->4082 4085 entropy = 0.0 samples = 14 value = [14, 0] class = No 4084->4085 4086 YRSWRKPA <= 10.5 entropy = 0.722 samples = 25 value = [20, 5] class = No 4084->4086 4087 SMKSTAT2_3.0 <= 0.5 entropy = 0.918 samples = 15 value = [10, 5] class = No 4086->4087 4096 entropy = 0.0 samples = 10 value = [10, 0] class = No 4086->4096 4088 BMI <= 2545.5 entropy = 0.779 samples = 13 value = [10, 3] class = No 4087->4088 4095 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4087->4095 4089 ASIMEDC_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 4088->4089 4094 entropy = 0.0 samples = 6 value = [6, 0] class = No 4088->4094 4090 JNTSYMP_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 4089->4090 4093 entropy = 0.0 samples = 3 value = [3, 0] class = No 4089->4093 4091 entropy = 0.0 samples = 1 value = [1, 0] class = No 4090->4091 4092 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4090->4092 4100 entropy = 0.0 samples = 39 value = [39, 0] class = No 4099->4100 4101 R_MARITL_4 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 4099->4101 4102 entropy = 0.0 samples = 1 value = [1, 0] class = No 4101->4102 4103 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4101->4103 4105 AHCNOYR2 <= 7.5 entropy = 0.918 samples = 6 value = [2, 4] class = Yes 4104->4105 4108 entropy = 0.0 samples = 6 value = [6, 0] class = No 4104->4108 4106 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 4105->4106 4107 entropy = 0.0 samples = 2 value = [2, 0] class = No 4105->4107 4110 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4109->4110 4111 entropy = 0.0 samples = 3 value = [3, 0] class = No 4109->4111 4113 entropy = 0.0 samples = 38 value = [38, 0] class = No 4112->4113 4114 ASIRETR_4.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 4112->4114 4115 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4114->4115 4116 entropy = 0.0 samples = 4 value = [4, 0] class = No 4114->4116 4118 BMI <= 2748.0 entropy = 0.377 samples = 767 value = [711, 56] class = No 4117->4118 4301 BEDDAYR <= 2.5 entropy = 0.231 samples = 560 value = [539, 21] class = No 4117->4301 4119 ASISTLV_4.0 <= 0.5 entropy = 0.386 samples = 741 value = [685, 56] class = No 4118->4119 4300 entropy = 0.0 samples = 26 value = [26, 0] class = No 4118->4300 4120 DIBPRE2_2.0 <= 0.5 entropy = 0.442 samples = 437 value = [397, 40] class = No 4119->4120 4243 ASIRETR_4.0 <= 0.5 entropy = 0.297 samples = 304 value = [288, 16] class = No 4119->4243 4121 BEDDAYR <= 1.5 entropy = 0.89 samples = 13 value = [9, 4] class = No 4120->4121 4130 BMI <= 2494.0 entropy = 0.419 samples = 424 value = [388, 36] class = No 4120->4130 4122 FLUVACYR_2.0 <= 0.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 4121->4122 4129 entropy = 0.0 samples = 5 value = [5, 0] class = No 4121->4129 4123 ASISTLV_2.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 4122->4123 4128 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4122->4128 4124 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 4123->4124 4127 entropy = 0.0 samples = 3 value = [3, 0] class = No 4123->4127 4125 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4124->4125 4126 entropy = 0.0 samples = 1 value = [1, 0] class = No 4124->4126 4131 BEDDAYR <= 3.5 entropy = 0.361 samples = 320 value = [298, 22] class = No 4130->4131 4204 ASICNHC_2.0 <= 0.5 entropy = 0.57 samples = 104 value = [90, 14] class = No 4130->4204 4132 DBHVCLN_2.0 <= 0.5 entropy = 0.32 samples = 292 value = [275, 17] class = No 4131->4132 4191 AHCNOYR2 <= 4.5 entropy = 0.677 samples = 28 value = [23, 5] class = No 4131->4191 4133 entropy = 0.0 samples = 44 value = [44, 0] class = No 4132->4133 4134 HIT1A_2.0 <= 0.5 entropy = 0.36 samples = 248 value = [231, 17] class = No 4132->4134 4135 AHCNOYR2 <= 6.5 entropy = 0.431 samples = 181 value = [165, 16] class = No 4134->4135 4186 PAINLB_2.0 <= 0.5 entropy = 0.112 samples = 67 value = [66, 1] class = No 4134->4186 4136 ASIRETR_4.0 <= 0.5 entropy = 0.456 samples = 167 value = [151, 16] class = No 4135->4136 4185 entropy = 0.0 samples = 14 value = [14, 0] class = No 4135->4185 4137 YRSWRKPA <= 0.5 entropy = 0.412 samples = 157 value = [144, 13] class = No 4136->4137 4178 R_MARITL_4 <= 0.5 entropy = 0.881 samples = 10 value = [7, 3] class = No 4136->4178 4138 entropy = 0.0 samples = 27 value = [27, 0] class = No 4137->4138 4139 YRSWRKPA <= 3.5 entropy = 0.469 samples = 130 value = [117, 13] class = No 4137->4139 4140 AHCNOYR2 <= 5.5 entropy = 0.669 samples = 40 value = [33, 7] class = No 4139->4140 4159 DIBREL_2.0 <= 0.5 entropy = 0.353 samples = 90 value = [84, 6] class = No 4139->4159 4141 BMI <= 2147.0 entropy = 0.562 samples = 38 value = [33, 5] class = No 4140->4141 4158 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4140->4158 4142 entropy = 0.0 samples = 11 value = [11, 0] class = No 4141->4142 4143 BMI <= 2159.5 entropy = 0.691 samples = 27 value = [22, 5] class = No 4141->4143 4144 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4143->4144 4145 AMDLONGR_1.0 <= 0.5 entropy = 0.619 samples = 26 value = [22, 4] class = No 4143->4145 4146 entropy = 0.0 samples = 7 value = [7, 0] class = No 4145->4146 4147 ASIRETR_2.0 <= 0.5 entropy = 0.742 samples = 19 value = [15, 4] class = No 4145->4147 4148 CHPAIN6M_4.0 <= 0.5 entropy = 0.414 samples = 12 value = [11, 1] class = No 4147->4148 4153 ASICNHC_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 4147->4153 4149 entropy = 0.0 samples = 10 value = [10, 0] class = No 4148->4149 4150 BMI <= 2430.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 4148->4150 4151 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4150->4151 4152 entropy = 0.0 samples = 1 value = [1, 0] class = No 4150->4152 4154 PAINLB_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 4153->4154 4157 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4153->4157 4155 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4154->4155 4156 entropy = 0.0 samples = 4 value = [4, 0] class = No 4154->4156 4160 YRSWRKPA <= 22.0 entropy = 0.684 samples = 22 value = [18, 4] class = No 4159->4160 4171 BMI <= 2044.5 entropy = 0.191 samples = 68 value = [66, 2] class = No 4159->4171 4161 YRSWRKPA <= 15.5 entropy = 0.811 samples = 16 value = [12, 4] class = No 4160->4161 4170 entropy = 0.0 samples = 6 value = [6, 0] class = No 4160->4170 4162 ASISTLV_2.0 <= 0.5 entropy = 0.592 samples = 14 value = [12, 2] class = No 4161->4162 4169 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4161->4169 4163 entropy = 0.0 samples = 7 value = [7, 0] class = No 4162->4163 4164 BMI <= 2119.0 entropy = 0.863 samples = 7 value = [5, 2] class = No 4162->4164 4165 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4164->4165 4166 PAINLB_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 4164->4166 4167 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4166->4167 4168 entropy = 0.0 samples = 5 value = [5, 0] class = No 4166->4168 4172 CHPAIN6M_3.0 <= 0.5 entropy = 0.523 samples = 17 value = [15, 2] class = No 4171->4172 4177 entropy = 0.0 samples = 51 value = [51, 0] class = No 4171->4177 4173 AHCNOYR2 <= 1.5 entropy = 0.337 samples = 16 value = [15, 1] class = No 4172->4173 4176 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4172->4176 4174 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4173->4174 4175 entropy = 0.0 samples = 15 value = [15, 0] class = No 4173->4175 4179 entropy = 0.0 samples = 4 value = [4, 0] class = No 4178->4179 4180 ASIMEDC_4.0 <= 0.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 4178->4180 4181 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4180->4181 4182 BMI <= 1945.5 entropy = 0.811 samples = 4 value = [3, 1] class = No 4180->4182 4183 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4182->4183 4184 entropy = 0.0 samples = 3 value = [3, 0] class = No 4182->4184 4187 BMI <= 2124.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 4186->4187 4190 entropy = 0.0 samples = 59 value = [59, 0] class = No 4186->4190 4188 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4187->4188 4189 entropy = 0.0 samples = 7 value = [7, 0] class = No 4187->4189 4192 YRSWRKPA <= 11.5 entropy = 0.874 samples = 17 value = [12, 5] class = No 4191->4192 4203 entropy = 0.0 samples = 11 value = [11, 0] class = No 4191->4203 4193 ASIRETR_2.0 <= 0.5 entropy = 0.722 samples = 15 value = [12, 3] class = No 4192->4193 4202 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4192->4202 4194 ASICNHC_2.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 4193->4194 4201 entropy = 0.0 samples = 6 value = [6, 0] class = No 4193->4201 4195 BEDDAYR <= 4.5 entropy = 1.0 samples = 6 value = [3, 3] class = No 4194->4195 4200 entropy = 0.0 samples = 3 value = [3, 0] class = No 4194->4200 4196 entropy = 0.0 samples = 2 value = [2, 0] class = No 4195->4196 4197 ASIRETR_4.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 4195->4197 4198 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4197->4198 4199 entropy = 0.0 samples = 1 value = [1, 0] class = No 4197->4199 4205 DBHVCLN_2.0 <= 0.5 entropy = 0.624 samples = 90 value = [76, 14] class = No 4204->4205 4242 entropy = 0.0 samples = 14 value = [14, 0] class = No 4204->4242 4206 DIBREL_2.0 <= 0.5 entropy = 0.881 samples = 20 value = [14, 6] class = No 4205->4206 4217 BMI <= 2742.5 entropy = 0.513 samples = 70 value = [62, 8] class = No 4205->4217 4207 ARTH1_2.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 4206->4207 4210 YRSWRKPA <= 15.0 entropy = 1.0 samples = 10 value = [5, 5] class = No 4206->4210 4208 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4207->4208 4209 entropy = 0.0 samples = 9 value = [9, 0] class = No 4207->4209 4211 AHCNOYR2 <= 3.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 4210->4211 4216 entropy = 0.0 samples = 3 value = [3, 0] class = No 4210->4216 4212 JNTSYMP_2.0 <= 0.5 entropy = 0.65 samples = 6 value = [1, 5] class = Yes 4211->4212 4215 entropy = 0.0 samples = 1 value = [1, 0] class = No 4211->4215 4213 entropy = 0.0 samples = 1 value = [1, 0] class = No 4212->4213 4214 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 4212->4214 4218 ASISTLV_2.0 <= 0.5 entropy = 0.439 samples = 66 value = [60, 6] class = No 4217->4218 4239 AHCNOYR2 <= 1.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 4217->4239 4219 YRSWRKPA <= 15.5 entropy = 0.551 samples = 47 value = [41, 6] class = No 4218->4219 4238 entropy = 0.0 samples = 19 value = [19, 0] class = No 4218->4238 4220 ASIRETR_2.0 <= 0.5 entropy = 0.391 samples = 39 value = [36, 3] class = No 4219->4220 4233 JNTSYMP_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 4219->4233 4221 SMKSTAT2_3.0 <= 0.5 entropy = 0.222 samples = 28 value = [27, 1] class = No 4220->4221 4226 FLUVACYR_2.0 <= 0.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 4220->4226 4222 entropy = 0.0 samples = 22 value = [22, 0] class = No 4221->4222 4223 BMI <= 2640.0 entropy = 0.65 samples = 6 value = [5, 1] class = No 4221->4223 4224 entropy = 0.0 samples = 5 value = [5, 0] class = No 4223->4224 4225 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4223->4225 4227 AMDLONGR_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 4226->4227 4232 entropy = 0.0 samples = 7 value = [7, 0] class = No 4226->4232 4228 DIBREL_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 4227->4228 4231 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4227->4231 4229 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4228->4229 4230 entropy = 0.0 samples = 2 value = [2, 0] class = No 4228->4230 4234 entropy = 0.0 samples = 4 value = [4, 0] class = No 4233->4234 4235 ASIMEDC_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 4233->4235 4236 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4235->4236 4237 entropy = 0.0 samples = 1 value = [1, 0] class = No 4235->4237 4240 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4239->4240 4241 entropy = 0.0 samples = 2 value = [2, 0] class = No 4239->4241 4244 YRSWRKPA <= 33.5 entropy = 0.439 samples = 77 value = [70, 7] class = No 4243->4244 4261 AHCNOYR2 <= 3.5 entropy = 0.241 samples = 227 value = [218, 9] class = No 4243->4261 4245 CHPAIN6M_4.0 <= 0.5 entropy = 0.353 samples = 75 value = [70, 5] class = No 4244->4245 4260 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4244->4260 4246 HIT1A_2.0 <= 0.5 entropy = 0.303 samples = 74 value = [70, 4] class = No 4245->4246 4259 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4245->4259 4247 BMI <= 2188.5 entropy = 0.408 samples = 49 value = [45, 4] class = No 4246->4247 4258 entropy = 0.0 samples = 25 value = [25, 0] class = No 4246->4258 4248 BMI <= 2147.5 entropy = 0.65 samples = 18 value = [15, 3] class = No 4247->4248 4253 AMDLONGR_2.0 <= 0.5 entropy = 0.206 samples = 31 value = [30, 1] class = No 4247->4253 4249 entropy = 0.0 samples = 13 value = [13, 0] class = No 4248->4249 4250 ASIMEDC_4.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 4248->4250 4251 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4250->4251 4252 entropy = 0.0 samples = 2 value = [2, 0] class = No 4250->4252 4254 entropy = 0.0 samples = 24 value = [24, 0] class = No 4253->4254 4255 YRSWRKPA <= 9.0 entropy = 0.592 samples = 7 value = [6, 1] class = No 4253->4255 4256 entropy = 0.0 samples = 6 value = [6, 0] class = No 4255->4256 4257 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4255->4257 4262 BMI <= 2724.5 entropy = 0.282 samples = 184 value = [175, 9] class = No 4261->4262 4299 entropy = 0.0 samples = 43 value = [43, 0] class = No 4261->4299 4263 YRSWRKPA <= 31.0 entropy = 0.26 samples = 182 value = [174, 8] class = No 4262->4263 4296 DOINGLWA_5.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 4262->4296 4264 BMI <= 2566.5 entropy = 0.3 samples = 150 value = [142, 8] class = No 4263->4264 4295 entropy = 0.0 samples = 32 value = [32, 0] class = No 4263->4295 4265 BMI <= 2559.5 entropy = 0.337 samples = 128 value = [120, 8] class = No 4264->4265 4294 entropy = 0.0 samples = 22 value = [22, 0] class = No 4264->4294 4266 BMI <= 2440.0 entropy = 0.308 samples = 127 value = [120, 7] class = No 4265->4266 4293 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4265->4293 4267 BMI <= 2406.0 entropy = 0.349 samples = 107 value = [100, 7] class = No 4266->4267 4292 entropy = 0.0 samples = 20 value = [20, 0] class = No 4266->4292 4268 BMI <= 1882.5 entropy = 0.25 samples = 96 value = [92, 4] class = No 4267->4268 4285 YRSWRKPA <= 4.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 4267->4285 4269 R_MARITL_4 <= 0.5 entropy = 0.619 samples = 13 value = [11, 2] class = No 4268->4269 4274 PDSICKA_2.0 <= 0.5 entropy = 0.164 samples = 83 value = [81, 2] class = No 4268->4274 4270 DOINGLWA_5.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 4269->4270 4273 entropy = 0.0 samples = 8 value = [8, 0] class = No 4269->4273 4271 entropy = 0.0 samples = 3 value = [3, 0] class = No 4270->4271 4272 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4270->4272 4275 entropy = 0.0 samples = 52 value = [52, 0] class = No 4274->4275 4276 SMKSTAT2_3.0 <= 0.5 entropy = 0.345 samples = 31 value = [29, 2] class = No 4274->4276 4277 AHCNOYR2 <= 2.5 entropy = 0.222 samples = 28 value = [27, 1] class = No 4276->4277 4282 DOINGLWA_5.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 4276->4282 4278 entropy = 0.0 samples = 21 value = [21, 0] class = No 4277->4278 4279 YRSWRKPA <= 1.0 entropy = 0.592 samples = 7 value = [6, 1] class = No 4277->4279 4280 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4279->4280 4281 entropy = 0.0 samples = 6 value = [6, 0] class = No 4279->4281 4283 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4282->4283 4284 entropy = 0.0 samples = 2 value = [2, 0] class = No 4282->4284 4286 entropy = 0.0 samples = 6 value = [6, 0] class = No 4285->4286 4287 WRKLYR4_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 4285->4287 4288 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4287->4288 4289 YRSWRKPA <= 25.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 4287->4289 4290 entropy = 0.0 samples = 2 value = [2, 0] class = No 4289->4290 4291 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4289->4291 4297 entropy = 0.0 samples = 1 value = [1, 0] class = No 4296->4297 4298 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4296->4298 4302 DBHVCLN_2.0 <= 0.5 entropy = 0.17 samples = 514 value = [501, 13] class = No 4301->4302 4351 ASIRETR_2.0 <= 0.5 entropy = 0.667 samples = 46 value = [38, 8] class = No 4301->4351 4303 ASICNHC_4.0 <= 0.5 entropy = 0.457 samples = 52 value = [47, 5] class = No 4302->4303 4320 BMI <= 2043.0 entropy = 0.126 samples = 462 value = [454, 8] class = No 4302->4320 4304 entropy = 0.0 samples = 24 value = [24, 0] class = No 4303->4304 4305 BMI <= 2605.5 entropy = 0.677 samples = 28 value = [23, 5] class = No 4303->4305 4306 BMI <= 2577.0 entropy = 0.831 samples = 19 value = [14, 5] class = No 4305->4306 4319 entropy = 0.0 samples = 9 value = [9, 0] class = No 4305->4319 4307 R_MARITL_4 <= 0.5 entropy = 0.672 samples = 17 value = [14, 3] class = No 4306->4307 4318 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4306->4318 4308 BMI <= 2329.5 entropy = 0.845 samples = 11 value = [8, 3] class = No 4307->4308 4317 entropy = 0.0 samples = 6 value = [6, 0] class = No 4307->4317 4309 entropy = 0.0 samples = 4 value = [4, 0] class = No 4308->4309 4310 DIBPRE2_2.0 <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 4308->4310 4311 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4310->4311 4312 SMKSTAT2_3.0 <= 0.5 entropy = 0.918 samples = 6 value = [4, 2] class = No 4310->4312 4313 entropy = 0.0 samples = 3 value = [3, 0] class = No 4312->4313 4314 ASIRETR_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 4312->4314 4315 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4314->4315 4316 entropy = 0.0 samples = 1 value = [1, 0] class = No 4314->4316 4321 BMI <= 2038.0 entropy = 0.35 samples = 76 value = [71, 5] class = No 4320->4321 4338 AMDLONGR_3.0 <= 0.5 entropy = 0.066 samples = 386 value = [383, 3] class = No 4320->4338 4322 YRSWRKPA <= 24.5 entropy = 0.247 samples = 73 value = [70, 3] class = No 4321->4322 4335 BEDDAYR <= 1.0 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 4321->4335 4323 AHCNOYR2 <= 1.5 entropy = 0.183 samples = 72 value = [70, 2] class = No 4322->4323 4334 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4322->4334 4324 BMI <= 1944.5 entropy = 0.391 samples = 26 value = [24, 2] class = No 4323->4324 4333 entropy = 0.0 samples = 46 value = [46, 0] class = No 4323->4333 4325 YRSWRKPA <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 4324->4325 4332 entropy = 0.0 samples = 18 value = [18, 0] class = No 4324->4332 4326 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4325->4326 4327 ASIRETR_4.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 4325->4327 4328 entropy = 0.0 samples = 4 value = [4, 0] class = No 4327->4328 4329 BMI <= 1912.0 entropy = 0.918 samples = 3 value = [2, 1] class = No 4327->4329 4330 entropy = 0.0 samples = 2 value = [2, 0] class = No 4329->4330 4331 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4329->4331 4336 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4335->4336 4337 entropy = 0.0 samples = 1 value = [1, 0] class = No 4335->4337 4339 BEDDAYR <= 1.5 entropy = 0.027 samples = 372 value = [371, 1] class = No 4338->4339 4346 FLUVACYR_2.0 <= 0.5 entropy = 0.592 samples = 14 value = [12, 2] class = No 4338->4346 4340 entropy = 0.0 samples = 336 value = [336, 0] class = No 4339->4340 4341 WRKLYR4_2.0 <= 0.5 entropy = 0.183 samples = 36 value = [35, 1] class = No 4339->4341 4342 entropy = 0.0 samples = 31 value = [31, 0] class = No 4341->4342 4343 ASICNHC_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 4341->4343 4344 entropy = 0.0 samples = 4 value = [4, 0] class = No 4343->4344 4345 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4343->4345 4347 ASISTLV_4.0 <= 0.5 entropy = 0.971 samples = 5 value = [3, 2] class = No 4346->4347 4350 entropy = 0.0 samples = 9 value = [9, 0] class = No 4346->4350 4348 entropy = 0.0 samples = 3 value = [3, 0] class = No 4347->4348 4349 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4347->4349 4352 BMI <= 2394.5 entropy = 0.764 samples = 36 value = [28, 8] class = No 4351->4352 4371 entropy = 0.0 samples = 10 value = [10, 0] class = No 4351->4371 4353 AHCNOYR2 <= 6.5 entropy = 0.902 samples = 22 value = [15, 7] class = No 4352->4353 4366 HYBPLEV_2.0 <= 0.5 entropy = 0.371 samples = 14 value = [13, 1] class = No 4352->4366 4354 BMI <= 2127.0 entropy = 0.811 samples = 20 value = [15, 5] class = No 4353->4354 4365 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4353->4365 4355 entropy = 0.0 samples = 6 value = [6, 0] class = No 4354->4355 4356 BMI <= 2158.5 entropy = 0.94 samples = 14 value = [9, 5] class = No 4354->4356 4357 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4356->4357 4358 CHPAIN6M_3.0 <= 0.5 entropy = 0.811 samples = 12 value = [9, 3] class = No 4356->4358 4359 AHCNOYR2 <= 1.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 4358->4359 4364 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4358->4364 4360 BMI <= 2283.0 entropy = 1.0 samples = 4 value = [2, 2] class = No 4359->4360 4363 entropy = 0.0 samples = 7 value = [7, 0] class = No 4359->4363 4361 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4360->4361 4362 entropy = 0.0 samples = 2 value = [2, 0] class = No 4360->4362 4367 entropy = 0.0 samples = 12 value = [12, 0] class = No 4366->4367 4368 JNTSYMP_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 4366->4368 4369 entropy = 0.0 samples = 1 value = [1, 0] class = No 4368->4369 4370 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4368->4370 4373 DBHVCLN_2.0 <= 0.5 entropy = 0.722 samples = 345 value = [276, 69] class = No 4372->4373 4508 YRSWRKPA <= 6.5 entropy = 0.404 samples = 199 value = [183, 16] class = No 4372->4508 4374 YRSWRKPA <= 21.5 entropy = 0.883 samples = 93 value = [65, 28] class = No 4373->4374 4415 AHCNOYR2 <= 7.0 entropy = 0.641 samples = 252 value = [211, 41] class = No 4373->4415 4375 HIT1A_2.0 <= 0.5 entropy = 0.953 samples = 75 value = [47, 28] class = No 4374->4375 4414 entropy = 0.0 samples = 18 value = [18, 0] class = No 4374->4414 4376 ASISTLV_2.0 <= 0.5 entropy = 0.997 samples = 49 value = [26, 23] class = No 4375->4376 4405 FLUVACYR_2.0 <= 0.5 entropy = 0.706 samples = 26 value = [21, 5] class = No 4375->4405 4377 AHCNOYR2 <= 1.5 entropy = 0.946 samples = 33 value = [21, 12] class = No 4376->4377 4396 SMKSTAT2_3.0 <= 0.5 entropy = 0.896 samples = 16 value = [5, 11] class = Yes 4376->4396 4378 AMDLONGR_1.0 <= 0.5 entropy = 0.863 samples = 7 value = [2, 5] class = Yes 4377->4378 4383 BMI <= 3032.0 entropy = 0.84 samples = 26 value = [19, 7] class = No 4377->4383 4379 YRSWRKPA <= 5.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 4378->4379 4382 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 4378->4382 4380 entropy = 0.0 samples = 2 value = [2, 0] class = No 4379->4380 4381 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4379->4381 4384 entropy = 0.0 samples = 8 value = [8, 0] class = No 4383->4384 4385 BMI <= 3118.5 entropy = 0.964 samples = 18 value = [11, 7] class = No 4383->4385 4386 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4385->4386 4387 YRSWRKPA <= 4.5 entropy = 0.896 samples = 16 value = [11, 5] class = No 4385->4387 4388 YRSWRKPA <= 3.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 4387->4388 4395 entropy = 0.0 samples = 6 value = [6, 0] class = No 4387->4395 4389 BEDDAYR <= 1.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 4388->4389 4394 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4388->4394 4390 AHCNOYR2 <= 2.5 entropy = 0.65 samples = 6 value = [5, 1] class = No 4389->4390 4393 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4389->4393 4391 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4390->4391 4392 entropy = 0.0 samples = 5 value = [5, 0] class = No 4390->4392 4397 BEDDAYR <= 2.0 entropy = 0.503 samples = 9 value = [1, 8] class = Yes 4396->4397 4400 BEDDAYR <= 0.5 entropy = 0.985 samples = 7 value = [4, 3] class = No 4396->4400 4398 entropy = 0.0 samples = 8 value = [0, 8] class = Yes 4397->4398 4399 entropy = 0.0 samples = 1 value = [1, 0] class = No 4397->4399 4401 HYPEV_2.0 <= 0.5 entropy = 0.722 samples = 5 value = [4, 1] class = No 4400->4401 4404 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4400->4404 4402 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4401->4402 4403 entropy = 0.0 samples = 4 value = [4, 0] class = No 4401->4403 4406 BEDDAYR <= 0.5 entropy = 1.0 samples = 10 value = [5, 5] class = No 4405->4406 4413 entropy = 0.0 samples = 16 value = [16, 0] class = No 4405->4413 4407 PDSICKA_2.0 <= 0.5 entropy = 0.863 samples = 7 value = [5, 2] class = No 4406->4407 4412 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4406->4412 4408 HYPEV_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 4407->4408 4411 entropy = 0.0 samples = 3 value = [3, 0] class = No 4407->4411 4409 entropy = 0.0 samples = 2 value = [2, 0] class = No 4408->4409 4410 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4408->4410 4416 AHEARST1_4.0 <= 0.5 entropy = 0.619 samples = 247 value = [209, 38] class = No 4415->4416 4505 ARTH1_2.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 4415->4505 4417 BMI <= 2871.5 entropy = 0.596 samples = 242 value = [207, 35] class = No 4416->4417 4502 BMI <= 3092.0 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 4416->4502 4418 BMI <= 2851.5 entropy = 0.857 samples = 32 value = [23, 9] class = No 4417->4418 4433 BMI <= 3409.5 entropy = 0.54 samples = 210 value = [184, 26] class = No 4417->4433 4419 HYPEV_2.0 <= 0.5 entropy = 0.61 samples = 20 value = [17, 3] class = No 4418->4419 4426 AHCNOYR2 <= 3.5 entropy = 1.0 samples = 12 value = [6, 6] class = No 4418->4426 4420 FLUVACYR_2.0 <= 0.5 entropy = 0.954 samples = 8 value = [5, 3] class = No 4419->4420 4425 entropy = 0.0 samples = 12 value = [12, 0] class = No 4419->4425 4421 entropy = 0.0 samples = 3 value = [3, 0] class = No 4420->4421 4422 AMDLONGR_1.0 <= 0.5 entropy = 0.971 samples = 5 value = [2, 3] class = Yes 4420->4422 4423 entropy = 0.0 samples = 2 value = [2, 0] class = No 4422->4423 4424 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4422->4424 4427 ASIMEDC_4.0 <= 0.5 entropy = 0.918 samples = 9 value = [6, 3] class = No 4426->4427 4432 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4426->4432 4428 CHPAIN6M_4.0 <= 0.5 entropy = 0.592 samples = 7 value = [6, 1] class = No 4427->4428 4431 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4427->4431 4429 entropy = 0.0 samples = 6 value = [6, 0] class = No 4428->4429 4430 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4428->4430 4434 YRSWRKPA <= 28.5 entropy = 0.456 samples = 177 value = [160, 17] class = No 4433->4434 4487 ASIRETR_2.0 <= 0.5 entropy = 0.845 samples = 33 value = [24, 9] class = No 4433->4487 4435 ASICNHC_4.0 <= 0.5 entropy = 0.493 samples = 158 value = [141, 17] class = No 4434->4435 4486 entropy = 0.0 samples = 19 value = [19, 0] class = No 4434->4486 4436 ASIMEDC_2.0 <= 0.5 entropy = 0.3 samples = 75 value = [71, 4] class = No 4435->4436 4451 ASIMEDC_4.0 <= 0.5 entropy = 0.626 samples = 83 value = [70, 13] class = No 4435->4451 4437 ASICNHC_2.0 <= 0.5 entropy = 0.146 samples = 48 value = [47, 1] class = No 4436->4437 4442 ASICNHC_2.0 <= 0.5 entropy = 0.503 samples = 27 value = [24, 3] class = No 4436->4442 4438 entropy = 0.0 samples = 40 value = [40, 0] class = No 4437->4438 4439 R_MARITL_4 <= 0.5 entropy = 0.544 samples = 8 value = [7, 1] class = No 4437->4439 4440 entropy = 0.0 samples = 7 value = [7, 0] class = No 4439->4440 4441 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4439->4441 4443 YRSWRKPA <= 23.0 entropy = 0.722 samples = 15 value = [12, 3] class = No 4442->4443 4450 entropy = 0.0 samples = 12 value = [12, 0] class = No 4442->4450 4444 AHCNOYR2 <= 1.5 entropy = 0.592 samples = 14 value = [12, 2] class = No 4443->4444 4449 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4443->4449 4445 HIT1A_2.0 <= 0.5 entropy = 1.0 samples = 4 value = [2, 2] class = No 4444->4445 4448 entropy = 0.0 samples = 10 value = [10, 0] class = No 4444->4448 4446 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4445->4446 4447 entropy = 0.0 samples = 2 value = [2, 0] class = No 4445->4447 4452 YRSWRKPA <= 13.5 entropy = 0.855 samples = 25 value = [18, 7] class = No 4451->4452 4469 BMI <= 2980.0 entropy = 0.48 samples = 58 value = [52, 6] class = No 4451->4469 4453 DBHVWLY_2.0 <= 0.5 entropy = 0.702 samples = 21 value = [17, 4] class = No 4452->4453 4466 HYBPLEV_2.0 <= 0.5 entropy = 0.811 samples = 4 value = [1, 3] class = Yes 4452->4466 4454 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4453->4454 4455 BEDDAYR <= 2.5 entropy = 0.61 samples = 20 value = [17, 3] class = No 4453->4455 4456 HIT1A_2.0 <= 0.5 entropy = 0.485 samples = 19 value = [17, 2] class = No 4455->4456 4465 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4455->4465 4457 SMKSTAT2_3.0 <= 0.5 entropy = 0.684 samples = 11 value = [9, 2] class = No 4456->4457 4464 entropy = 0.0 samples = 8 value = [8, 0] class = No 4456->4464 4458 DIBREL_2.0 <= 0.5 entropy = 0.469 samples = 10 value = [9, 1] class = No 4457->4458 4463 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4457->4463 4459 FLUVACYR_2.0 <= 0.5 entropy = 1.0 samples = 2 value = [1, 1] class = No 4458->4459 4462 entropy = 0.0 samples = 8 value = [8, 0] class = No 4458->4462 4460 entropy = 0.0 samples = 1 value = [1, 0] class = No 4459->4460 4461 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4459->4461 4467 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4466->4467 4468 entropy = 0.0 samples = 1 value = [1, 0] class = No 4466->4468 4470 entropy = 0.0 samples = 18 value = [18, 0] class = No 4469->4470 4471 CHLEV_2.0 <= 0.5 entropy = 0.61 samples = 40 value = [34, 6] class = No 4469->4471 4472 ASIRETR_4.0 <= 0.5 entropy = 0.971 samples = 10 value = [6, 4] class = No 4471->4472 4479 HYPEV_2.0 <= 0.5 entropy = 0.353 samples = 30 value = [28, 2] class = No 4471->4479 4473 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4472->4473 4474 YRSWRKPA <= 9.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 4472->4474 4475 DOINGLWA_5.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 4474->4475 4478 entropy = 0.0 samples = 5 value = [5, 0] class = No 4474->4478 4476 entropy = 0.0 samples = 1 value = [1, 0] class = No 4475->4476 4477 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4475->4477 4480 BMI <= 3149.0 entropy = 0.863 samples = 7 value = [5, 2] class = No 4479->4480 4485 entropy = 0.0 samples = 23 value = [23, 0] class = No 4479->4485 4481 entropy = 0.0 samples = 4 value = [4, 0] class = No 4480->4481 4482 DIBPRE2_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 4480->4482 4483 entropy = 0.0 samples = 1 value = [1, 0] class = No 4482->4483 4484 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4482->4484 4488 ARTH1_2.0 <= 0.5 entropy = 0.454 samples = 21 value = [19, 2] class = No 4487->4488 4495 YRSWRKPA <= 20.0 entropy = 0.98 samples = 12 value = [5, 7] class = Yes 4487->4495 4489 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4488->4489 4490 AMDLONGR_2.0 <= 0.5 entropy = 0.286 samples = 20 value = [19, 1] class = No 4488->4490 4491 entropy = 0.0 samples = 17 value = [17, 0] class = No 4490->4491 4492 HIT1A_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 4490->4492 4493 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4492->4493 4494 entropy = 0.0 samples = 2 value = [2, 0] class = No 4492->4494 4496 PDSICKA_2.0 <= 0.5 entropy = 0.764 samples = 9 value = [2, 7] class = Yes 4495->4496 4501 entropy = 0.0 samples = 3 value = [3, 0] class = No 4495->4501 4497 entropy = 0.0 samples = 6 value = [0, 6] class = Yes 4496->4497 4498 JNTSYMP_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 4496->4498 4499 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4498->4499 4500 entropy = 0.0 samples = 2 value = [2, 0] class = No 4498->4500 4503 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4502->4503 4504 entropy = 0.0 samples = 2 value = [2, 0] class = No 4502->4504 4506 entropy = 0.0 samples = 2 value = [2, 0] class = No 4505->4506 4507 entropy = 0.0 samples = 3 value = [0, 3] class = Yes 4505->4507 4509 ASIMEDC_4.0 <= 0.5 entropy = 0.222 samples = 112 value = [108, 4] class = No 4508->4509 4530 BMI <= 3229.5 entropy = 0.579 samples = 87 value = [75, 12] class = No 4508->4530 4510 AMDLONGR_1.0 <= 0.5 entropy = 0.326 samples = 67 value = [63, 4] class = No 4509->4510 4529 entropy = 0.0 samples = 45 value = [45, 0] class = No 4509->4529 4511 entropy = 0.0 samples = 20 value = [20, 0] class = No 4510->4511 4512 PAINLB_2.0 <= 0.5 entropy = 0.42 samples = 47 value = [43, 4] class = No 4510->4512 4513 entropy = 0.0 samples = 15 value = [15, 0] class = No 4512->4513 4514 FLUVACYR_2.0 <= 0.5 entropy = 0.544 samples = 32 value = [28, 4] class = No 4512->4514 4515 entropy = 0.0 samples = 9 value = [9, 0] class = No 4514->4515 4516 BEDDAYR <= 0.5 entropy = 0.667 samples = 23 value = [19, 4] class = No 4514->4516 4517 HYBPLEV_2.0 <= 0.5 entropy = 0.787 samples = 17 value = [13, 4] class = No 4516->4517 4528 entropy = 0.0 samples = 6 value = [6, 0] class = No 4516->4528 4518 ASISTLV_2.0 <= 0.5 entropy = 0.696 samples = 16 value = [13, 3] class = No 4517->4518 4527 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4517->4527 4519 BMI <= 2931.0 entropy = 0.918 samples = 9 value = [6, 3] class = No 4518->4519 4526 entropy = 0.0 samples = 7 value = [7, 0] class = No 4518->4526 4520 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4519->4520 4521 YRSWRKPA <= 0.5 entropy = 0.811 samples = 8 value = [6, 2] class = No 4519->4521 4522 PDSICKA_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [1, 2] class = Yes 4521->4522 4525 entropy = 0.0 samples = 5 value = [5, 0] class = No 4521->4525 4523 entropy = 0.0 samples = 2 value = [0, 2] class = Yes 4522->4523 4524 entropy = 0.0 samples = 1 value = [1, 0] class = No 4522->4524 4531 DIBREL_2.0 <= 0.5 entropy = 0.362 samples = 58 value = [54, 4] class = No 4530->4531 4540 BMI <= 3729.0 entropy = 0.85 samples = 29 value = [21, 8] class = No 4530->4540 4532 BMI <= 3008.5 entropy = 0.787 samples = 17 value = [13, 4] class = No 4531->4532 4539 entropy = 0.0 samples = 41 value = [41, 0] class = No 4531->4539 4533 AHCNOYR2 <= 1.5 entropy = 1.0 samples = 8 value = [4, 4] class = No 4532->4533 4538 entropy = 0.0 samples = 9 value = [9, 0] class = No 4532->4538 4534 entropy = 0.0 samples = 3 value = [3, 0] class = No 4533->4534 4535 CHPAIN6M_3.0 <= 0.5 entropy = 0.722 samples = 5 value = [1, 4] class = Yes 4533->4535 4536 entropy = 0.0 samples = 4 value = [0, 4] class = Yes 4535->4536 4537 entropy = 0.0 samples = 1 value = [1, 0] class = No 4535->4537 4541 ASISTLV_4.0 <= 0.5 entropy = 0.971 samples = 20 value = [12, 8] class = No 4540->4541 4552 entropy = 0.0 samples = 9 value = [9, 0] class = No 4540->4552 4542 ASISTLV_2.0 <= 0.5 entropy = 0.811 samples = 8 value = [2, 6] class = Yes 4541->4542 4547 DBHVWLY_2.0 <= 0.5 entropy = 0.65 samples = 12 value = [10, 2] class = No 4541->4547 4543 entropy = 0.0 samples = 5 value = [0, 5] class = Yes 4542->4543 4544 DBHVCLN_2.0 <= 0.5 entropy = 0.918 samples = 3 value = [2, 1] class = No 4542->4544 4545 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4544->4545 4546 entropy = 0.0 samples = 2 value = [2, 0] class = No 4544->4546 4548 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4547->4548 4549 YRSWRKPA <= 8.5 entropy = 0.439 samples = 11 value = [10, 1] class = No 4547->4549 4550 entropy = 0.0 samples = 1 value = [0, 1] class = Yes 4549->4550 4551 entropy = 0.0 samples = 10 value = [10, 0] class = No 4549->4551
In [115]:
system(dot -Tpng tree2.dot -o dtree2.png)
Out[115]:
['dot: graph is too large for cairo-renderer bitmaps. Scaling by 0.319404 to fit']
In [116]:
from IPython.display import Image
Image(filename='dtree2.png', width=800)
Out[116]:
In [117]:
#Find the best percentile for feature selection using cross-validation
from sklearn import cross_validation
dt = tree.DecisionTreeClassifier(criterion='entropy')

percentiles = range(1, 100, 5)
results = []
for i in range(1, 100, 5):
    fs = feature_selection.SelectPercentile(feature_selection.chi2, percentile=i)
    X_train_fs = fs.fit_transform(X_train, y_train)
    scores = cross_validation.cross_val_score(dt, X_train_fs, y_train, cv=5)
    print i,scores.mean()
    results = np.append(results, scores.mean())

# optimal_percentile = np.where(results == results.max())[0]
# print "Optimal percentile of features:{0}".format(percentiles[optimal_percentile]), "\n"
# optimal_num_features = int(percentiles[optimal_percentile]*len(X.columns)/100)
# print "Optimal number of features:{0}".format(optimal_num_features), "\n"

optimal_percentil = int(np.where(results == results.max())[0])
print "Optimal percentile of features is: ", percentiles[optimal_percentil]

#optimal_num_features = percentiles[optimal_percentile]*len(X.columns)/100
#optimal_num_features = int(math.floor(percentiles[optimal_percentil]*X.shape[1]/100))
optimal_num_features = int((percentiles[optimal_percentil]*X.shape[1]/100))
print "Optimal number of features is: ", optimal_num_features



# Plot percentile of features VS. cross-validation scores
import pylab as pl
pl.figure()
pl.xlabel("Percentage of features selected")
pl.ylabel("Cross validation accuracy")
pl.plot(percentiles,results)
1 0.6573448546739985
6 0.7065200314218381
11 0.7055773762765122
16 0.7063629222309504
21 0.711311861743912
26 0.7100549882168108
31 0.7142969363707777
36 0.715553809897879
41 0.7186174391201885
46 0.7135899450117832
51 0.7144540455616653
56 0.711783189316575
61 0.7150039277297722
66 0.7124901806755695
71 0.7142183817753338
76 0.7171249018067557
81 0.712725844461901
86 0.7088766692851532
91 0.7124116260801256
96 0.7117046347211312
Optimal percentile of features is:  41
Optimal number of features is:  58
Out[117]:
[<matplotlib.lines.Line2D at 0x18a25278>]
In [118]:
#Impact of max-depth
In [119]:
from sklearn.cross_validation import KFold

def calc_params(X, y, clf, param_values, param_name, K):
    
    # Convert input to Numpy arrays
    X = np.array(X)
    y = np.array(y)

    # initialize training and testing scores with zeros
    train_scores = np.zeros(len(param_values))
    test_scores = np.zeros(len(param_values))
    
    # iterate over the different parameter values
    for i, param_value in enumerate(param_values):
        print param_name, ' = ', param_value
        
        # set classifier parameters
        clf.set_params(**{param_name:param_value})
        
        # initialize the K scores obtained for each fold
        k_train_scores = np.zeros(K)
        k_test_scores = np.zeros(K)
        
        # create KFold cross validation
        cv = KFold(len(X), K, shuffle=True, random_state=0)
        
        # iterate over the K folds
        for j, (train, test) in enumerate(cv):
            # fit the classifier in the corresponding fold
            # and obtain the corresponding accuracy scores on train and test sets
            clf.fit([X[k] for k in train], y[train])
            k_train_scores[j] = clf.score([X[k] for k in train], y[train])
            k_test_scores[j] = clf.score([X[k] for k in test], y[test])
            
        # store the mean of the K fold scores
        train_scores[i] = np.mean(k_train_scores)
        test_scores[i] = np.mean(k_test_scores)
       
    # plot the training and testing scores in a log scale
    plt.plot(param_values, train_scores, label='Train', alpha=0.4, lw=2, c='b')
    plt.plot(param_values, test_scores, label='X-Val', alpha=0.4, lw=2, c='g')
    plt.legend(loc=7)
    plt.xlabel(param_name + " values")
    plt.ylabel("Mean cross validation accuracy")

    # return the training and testing scores on each parameter value
    return train_scores, test_scores
In [120]:
# Let's create an evenly spaced range of numbers in a specified interval
md = np.linspace(1, 40, 20)
md = np.array([int(e) for e in md])
print md
[ 1  3  5  7  9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 40]
In [121]:
train_scores, test_scores = calc_params(X_train, y_train, dt, md, 'max_depth', 5)
max_depth  =  1
max_depth  =  3
max_depth  =  5
max_depth  =  7
max_depth  =  9
max_depth  =  11
max_depth  =  13
max_depth  =  15
max_depth  =  17
max_depth  =  19
max_depth  =  21
max_depth  =  23
max_depth  =  25
max_depth  =  27
max_depth  =  29
max_depth  =  31
max_depth  =  33
max_depth  =  35
max_depth  =  37
max_depth  =  40
In [122]:
#max_depth = 4 looks the best
In [123]:
#min number of samples allowed at a leaf node
In [124]:
msl = np.linspace(1, 30, 15)
msl = np.array([int(e) for e in msl])

dt = tree.DecisionTreeClassifier(criterion='entropy')
train_scores, test_scores = calc_params(X_train, y_train, dt, msl, 'min_samples_leaf', 5)
min_samples_leaf  =  1
min_samples_leaf  =  3
min_samples_leaf  =  5
min_samples_leaf  =  7
min_samples_leaf  =  9
min_samples_leaf  =  11
min_samples_leaf  =  13
min_samples_leaf  =  15
min_samples_leaf  =  17
min_samples_leaf  =  19
min_samples_leaf  =  21
min_samples_leaf  =  23
min_samples_leaf  =  25
min_samples_leaf  =  27
min_samples_leaf  =  30
In [125]:
#min_samples_leaf should be between 10 and 15 
In [126]:
#Grid Search allows us to more systemiatically explore different combinations of multiple parameters
In [127]:
#from sklearn.grid_search import GridSearchCV
from sklearn.model_selection import GridSearchCV


dt = tree.DecisionTreeClassifier()

# parameters = {
#     'criterion': ['entropy','gini'],
#     'max_depth': np.linspace(1, 20, 10),
#     'min_samples_leaf': np.linspace(10, 15, 5),
#     'min_samples_split': np.linspace(10, 15, 5)
# }

parameters = {
    'criterion': ['entropy','gini'],
    'max_depth': [1,2,3,4,5,6,8,10],
    'min_samples_leaf': [2,4,6,8,10,12,14,16,18,20,],
    'min_samples_split': [2,4,6,8,10,12,14,16,18,20]
}

gs = GridSearchCV(estimator=dt, param_grid=parameters, verbose=1, cv=5,refit=True, n_jobs = -1)
In [128]:
%time
gs.fit(X_train, y_train)
gs.best_params_, gs.best_score_
Wall time: 0 ns
Fitting 5 folds for each of 1600 candidates, totalling 8000 fits
[Parallel(n_jobs=-1)]: Done  42 tasks      | elapsed:    3.2s
[Parallel(n_jobs=-1)]: Done 311 tasks      | elapsed:    9.9s
[Parallel(n_jobs=-1)]: Done 811 tasks      | elapsed:   23.4s
[Parallel(n_jobs=-1)]: Done 1511 tasks      | elapsed:   46.4s
[Parallel(n_jobs=-1)]: Done 2411 tasks      | elapsed:  1.5min
[Parallel(n_jobs=-1)]: Done 3511 tasks      | elapsed:  2.6min
[Parallel(n_jobs=-1)]: Done 4582 tasks      | elapsed:  3.6min
[Parallel(n_jobs=-1)]: Done 6082 tasks      | elapsed:  4.5min
[Parallel(n_jobs=-1)]: Done 7782 tasks      | elapsed:  6.3min
[Parallel(n_jobs=-1)]: Done 8000 out of 8000 | elapsed:  6.6min finished
Out[128]:
({'criterion': 'entropy',
  'max_depth': 1,
  'min_samples_leaf': 2,
  'min_samples_split': 2},
 0.8069128043990573)
In [129]:
# Note: best parameters results change most of the time

# [Parallel(n_jobs=1)]: Done 8000 out of 8000 | elapsed:  2.9min finished

# ({'criterion': 'gini',
#   'max_depth': 5,
#   'min_samples_leaf': 20,
#   'min_samples_split': 2},
#  0.8076197957580519)

dt = tree.DecisionTreeClassifier(criterion='gini', max_depth=5, min_samples_leaf=20, min_samples_split=2)

dt.fit(X_train, y_train)
measure_performance(X_test, y_test, dt, show_confussion_matrix=False, show_classification_report=True)
Accuracy:0.801 

Classification report
             precision    recall  f1-score   support

          0       0.82      0.90      0.86      2140
          1       0.75      0.59      0.66      1043

avg / total       0.80      0.80      0.79      3183


In [130]:
from sklearn.tree import export_graphviz
export_graphviz(dt,out_file='treefinal.dot', feature_names=X_train.columns)
In [131]:
import graphviz

with open("treefinal.dot") as f:
    dot_graph = f.read()
graphviz.Source(dot_graph)
Out[131]:
Tree 0 DBHVCLY_2.0 <= 0.5 gini = 0.443 samples = 12730 value = [8520, 4210] 1 BMI <= 2815.5 gini = 0.349 samples = 3188 value = [718, 2470] 0->1 True 32 FLA1AR_2 <= 0.5 gini = 0.298 samples = 9542 value = [7802, 1740] 0->32 False 2 DBHVPAN_2.0 <= 0.5 gini = 0.443 samples = 1032 value = [342, 690] 1->2 17 DBHVWLY_2.0 <= 0.5 gini = 0.288 samples = 2156 value = [376, 1780] 1->17 3 CANEV_2.0 <= 0.5 gini = 0.403 samples = 709 value = [198, 511] 2->3 10 ASISTLV_4.0 <= 0.5 gini = 0.494 samples = 323 value = [144, 179] 2->10 4 ASICPUSE_4.0 <= 0.5 gini = 0.492 samples = 87 value = [38, 49] 3->4 7 AHCNOYR2 <= 5.5 gini = 0.382 samples = 622 value = [160, 462] 3->7 5 gini = 0.444 samples = 21 value = [14, 7] 4->5 6 gini = 0.463 samples = 66 value = [24, 42] 4->6 8 gini = 0.4 samples = 546 value = [151, 395] 7->8 9 gini = 0.209 samples = 76 value = [9, 67] 7->9 11 DBHVCLN_2.0 <= 0.5 gini = 0.47 samples = 220 value = [83, 137] 10->11 14 CHLEV_2.0 <= 0.5 gini = 0.483 samples = 103 value = [61, 42] 10->14 12 gini = 0.496 samples = 130 value = [59, 71] 11->12 13 gini = 0.391 samples = 90 value = [24, 66] 11->13 15 gini = 0.499 samples = 57 value = [27, 30] 14->15 16 gini = 0.386 samples = 46 value = [34, 12] 14->16 18 BMI <= 2914.0 gini = 0.159 samples = 667 value = [58, 609] 17->18 25 BMI <= 3533.5 gini = 0.336 samples = 1489 value = [318, 1171] 17->25 19 REGION_3 <= 0.5 gini = 0.305 samples = 48 value = [9, 39] 18->19 22 BEDDAYR <= 3.5 gini = 0.146 samples = 619 value = [49, 570] 18->22 20 gini = 0.426 samples = 26 value = [8, 18] 19->20 21 gini = 0.087 samples = 22 value = [1, 21] 19->21 23 gini = 0.166 samples = 503 value = [46, 457] 22->23 24 gini = 0.05 samples = 116 value = [3, 113] 22->24 26 DBHVPAN_2.0 <= 0.5 gini = 0.365 samples = 1108 value = [266, 842] 25->26 29 ASICPUSE_4.0 <= 0.5 gini = 0.236 samples = 381 value = [52, 329] 25->29 27 gini = 0.332 samples = 765 value = [161, 604] 26->27 28 gini = 0.425 samples = 343 value = [105, 238] 26->28 30 gini = 0.313 samples = 139 value = [27, 112] 29->30 31 gini = 0.185 samples = 242 value = [25, 217] 29->31 33 DBHVPAN_2.0 <= 0.5 gini = 0.402 samples = 3355 value = [2422, 933] 32->33 48 DBHVPAN_2.0 <= 0.5 gini = 0.227 samples = 6187 value = [5380, 807] 32->48 34 BEDDAYR <= 3.5 gini = 0.45 samples = 1734 value = [1141, 593] 33->34 41 DBHVCLN_2.0 <= 0.5 gini = 0.332 samples = 1621 value = [1281, 340] 33->41 35 HYPEV_2.0 <= 0.5 gini = 0.421 samples = 1372 value = [959, 413] 34->35 38 AHCNOYR2 <= 2.5 gini = 0.5 samples = 362 value = [182, 180] 34->38 36 gini = 0.47 samples = 605 value = [376, 229] 35->36 37 gini = 0.365 samples = 767 value = [583, 184] 35->37 39 gini = 0.407 samples = 74 value = [53, 21] 38->39 40 gini = 0.495 samples = 288 value = [129, 159] 38->40 42 FLUVACYR_2.0 <= 0.5 gini = 0.436 samples = 373 value = [253, 120] 41->42 45 DIBPRE2_2.0 <= 0.5 gini = 0.29 samples = 1248 value = [1028, 220] 41->45 43 gini = 0.477 samples = 209 value = [127, 82] 42->43 44 gini = 0.356 samples = 164 value = [126, 38] 42->44 46 gini = 0.446 samples = 110 value = [73, 37] 45->46 47 gini = 0.27 samples = 1138 value = [955, 183] 45->47 49 AHCNOYR2 <= 1.5 gini = 0.285 samples = 3311 value = [2740, 571] 48->49 56 DBHVCLN_2.0 <= 0.5 gini = 0.151 samples = 2876 value = [2640, 236] 48->56 50 AMDLONGR_1.0 <= 0.5 gini = 0.191 samples = 1242 value = [1109, 133] 49->50 53 BMI <= 2580.5 gini = 0.334 samples = 2069 value = [1631, 438] 49->53 51 gini = 0.122 samples = 692 value = [647, 45] 50->51 52 gini = 0.269 samples = 550 value = [462, 88] 50->52 54 gini = 0.277 samples = 1055 value = [880, 175] 53->54 55 gini = 0.384 samples = 1014 value = [751, 263] 53->55 57 AHAYFYR_2.0 <= 0.5 gini = 0.254 samples = 456 value = [388, 68] 56->57 60 AHCNOYR2 <= 0.5 gini = 0.129 samples = 2420 value = [2252, 168] 56->60 58 gini = 0.463 samples = 33 value = [21, 12] 57->58 59 gini = 0.23 samples = 423 value = [367, 56] 57->59 61 gini = 0.039 samples = 451 value = [442, 9] 60->61 62 gini = 0.148 samples = 1969 value = [1810, 159] 60->62
In [132]:
system(dot -Tpng treefinal.dot -o treefinal.png)
Out[132]:
[]
In [133]:
from IPython.display import Image
Image(filename='treefinal.png', width=800)
Out[133]:
In [134]:
print(X_train.columns.values)
['SEX_2' 'R_MARITL_2' 'R_MARITL_3' 'R_MARITL_4' 'MRACRPI2_2' 'MRACRPI2_3' 'MRACRPI2_4' 'REGION_2' 'REGION_3' 'REGION_4' 'PAR_STAT_2' 'PAR_STAT_3' 'DOINGLWA_2.0' 'DOINGLWA_3.0' 'DOINGLWA_4.0' 'DOINGLWA_5.0' 'SUPERVIS_2.0' 'WRKCATA_2.0' 'WRKCATA_3.0' 'WRKCATA_4.0' 'WRKCATA_5.0' 'WRKCATA_6.0' 'HOURPDA_2.0' 'PDSICKA_2.0'
 'WRKLYR4_1.0' 'WRKLYR4_2.0' 'HYPEV_2.0' 'HYBPLEV_2.0' 'HYBPLEV_3.0' 'HYBPLEV_4.0' 'HYBPLEV_5.0' 'CHLEV_2.0' 'CHDEV_2.0' 'MIEV_2.0' 'STREV_2.0' 'COPDEV_2.0' 'AASMEV_2.0' 'ULCEV_2.0' 'CANEV_2.0' 'DBHVCLY_2.0' 'DBHVWLY_2.0' 'DBHVPAN_2.0' 'DBHVCLN_2.0' 'DBHVWLN_2.0' 'DIBREL_2.0' 'DIBEV1_3.0' 'DIBPRE2_2.0' 'EPILEP1_2.0'
 'AHAYFYR_2.0' 'SINYR_2.0' 'CBRCHYR_2.0' 'KIDWKYR_2.0' 'LIVYR_2.0' 'JNTSYMP_2.0' 'ARTH1_2.0' 'PAINECK_2.0' 'PAINLB_2.0' 'PAINFACE_2.0' 'AMIGR_2.0' 'ACOLD2W_2.0' 'AINTIL2W_2.0' 'AHEARST1_2.0' 'AHEARST1_3.0' 'AHEARST1_4.0' 'AHEARST1_5.0' 'AHEARST1_6.0' 'AVISION_2.0' 'VIM_GLEV_2.0' 'VIM_MDEV_2.0' 'VIMGLASS_2.0'
 'AVISACT_2.0' 'CHPAIN6M_2.0' 'CHPAIN6M_3.0' 'CHPAIN6M_4.0' 'AHSTATYR_2.0' 'AHSTATYR_3.0' 'FLA1AR_2' 'FLA1AR_3' 'SPECEQ_2.0' 'ALC1YR_2.0' 'CIGAREV2_2.0' 'ECIGEV2_2.0' 'SMKSTAT2_2.0' 'SMKSTAT2_3.0' 'SMKSTAT2_4.0' 'APLKIND_2.0' 'APLKIND_3.0' 'APLKIND_4.0' 'APLKIND_5.0' 'APLKIND_6.0' 'AWORPAY_2.0' 'AWORPAY_3.0'
 'ADNLONG2_1.0' 'ADNLONG2_2.0' 'ADNLONG2_3.0' 'ADNLONG2_4.0' 'ADNLONG2_5.0' 'ASRGYR_2.0' 'AMDLONGR_1.0' 'AMDLONGR_2.0' 'AMDLONGR_3.0' 'AMDLONGR_4.0' 'AMDLONGR_5.0' 'HIT1A_2.0' 'HIT2A_2.0' 'HIT3A_2.0' 'HIT4A_2.0' 'FLUVACYR_2.0' 'LIVEV_2.0' 'ASICPUSE_2.0' 'ASICPUSE_3.0' 'ASICPUSE_4.0' 'ASIRETR_2.0' 'ASIRETR_3.0'
 'ASIRETR_4.0' 'ASIMEDC_2.0' 'ASIMEDC_3.0' 'ASIMEDC_4.0' 'ASISTLV_2.0' 'ASISTLV_3.0' 'ASISTLV_4.0' 'ASICNHC_2.0' 'ASICNHC_3.0' 'ASICNHC_4.0' 'AWEBUSE_2.0' 'YTQU_YG1_2.0' 'ALCSTAT_2' 'ALCSTAT_3' 'ALCSTAT_5' 'ALCSTAT_6' 'ALCSTAT_7' 'ALCSTAT_8' 'ALCSTAT_9' 'ALCSTAT_10' 'YRSWRKPA' 'ASISLEEP' 'AHEIGHT' 'BMI' 'BEDDAYR'
 'CLCKTP' 'AHCNOYR2' 'LOCALL1B']
In [135]:
dt = tree.DecisionTreeClassifier(criterion='entropy', max_depth=4, min_samples_leaf=10, min_samples_split=2)

dt.fit(X_train, y_train)
measure_performance(X_test, y_test, dt, show_confussion_matrix=True, show_classification_report=True)
Accuracy:0.803 

Classification report
             precision    recall  f1-score   support

          0       0.81      0.92      0.86      2140
          1       0.78      0.56      0.65      1043

avg / total       0.80      0.80      0.79      3183


Confussion matrix
[[1973  167]
 [ 459  584]] 

In [136]:
dt
Out[136]:
DecisionTreeClassifier(class_weight=None, criterion='entropy', max_depth=4,
            max_features=None, max_leaf_nodes=None,
            min_impurity_decrease=0.0, min_impurity_split=None,
            min_samples_leaf=10, min_samples_split=2,
            min_weight_fraction_leaf=0.0, presort=False, random_state=None,
            splitter='best')
In [137]:
dt.get_params
Out[137]:
<bound method DecisionTreeClassifier.get_params of DecisionTreeClassifier(class_weight=None, criterion='entropy', max_depth=4,
            max_features=None, max_leaf_nodes=None,
            min_impurity_decrease=0.0, min_impurity_split=None,
            min_samples_leaf=10, min_samples_split=2,
            min_weight_fraction_leaf=0.0, presort=False, random_state=None,
            splitter='best')>
In [138]:
from sklearn.tree import export_graphviz
export_graphviz(dt,out_file='treefinal2.dot', feature_names=X_train.columns)
In [139]:
import graphviz

with open("treefinal2.dot") as f:
    dot_graph = f.read()
graphviz.Source(dot_graph)
Out[139]:
Tree 0 DBHVCLY_2.0 <= 0.5 entropy = 0.916 samples = 12730 value = [8520, 4210] 1 BMI <= 2815.5 entropy = 0.77 samples = 3188 value = [718, 2470] 0->1 True 16 FLA1AR_2 <= 0.5 entropy = 0.685 samples = 9542 value = [7802, 1740] 0->16 False 2 DBHVPAN_2.0 <= 0.5 entropy = 0.916 samples = 1032 value = [342, 690] 1->2 9 DBHVWLY_2.0 <= 0.5 entropy = 0.668 samples = 2156 value = [376, 1780] 1->9 3 CANEV_2.0 <= 0.5 entropy = 0.854 samples = 709 value = [198, 511] 2->3 6 ASISTLV_4.0 <= 0.5 entropy = 0.992 samples = 323 value = [144, 179] 2->6 4 entropy = 0.988 samples = 87 value = [38, 49] 3->4 5 entropy = 0.823 samples = 622 value = [160, 462] 3->5 7 entropy = 0.956 samples = 220 value = [83, 137] 6->7 8 entropy = 0.975 samples = 103 value = [61, 42] 6->8 10 AHCNOYR2 <= 7.5 entropy = 0.426 samples = 667 value = [58, 609] 9->10 13 BMI <= 3533.5 entropy = 0.748 samples = 1489 value = [318, 1171] 9->13 11 entropy = 0.453 samples = 610 value = [58, 552] 10->11 12 entropy = 0.0 samples = 57 value = [0, 57] 10->12 14 entropy = 0.795 samples = 1108 value = [266, 842] 13->14 15 entropy = 0.575 samples = 381 value = [52, 329] 13->15 17 DBHVPAN_2.0 <= 0.5 entropy = 0.853 samples = 3355 value = [2422, 933] 16->17 24 DBHVPAN_2.0 <= 0.5 entropy = 0.559 samples = 6187 value = [5380, 807] 16->24 18 BEDDAYR <= 3.5 entropy = 0.927 samples = 1734 value = [1141, 593] 17->18 21 DBHVCLN_2.0 <= 0.5 entropy = 0.741 samples = 1621 value = [1281, 340] 17->21 19 entropy = 0.883 samples = 1372 value = [959, 413] 18->19 20 entropy = 1.0 samples = 362 value = [182, 180] 18->20 22 entropy = 0.906 samples = 373 value = [253, 120] 21->22 23 entropy = 0.672 samples = 1248 value = [1028, 220] 21->23 25 AMDLONGR_1.0 <= 0.5 entropy = 0.663 samples = 3311 value = [2740, 571] 24->25 28 AHCNOYR2 <= 0.5 entropy = 0.409 samples = 2876 value = [2640, 236] 24->28 26 entropy = 0.45 samples = 967 value = [876, 91] 25->26 27 entropy = 0.731 samples = 2344 value = [1864, 480] 25->27 29 entropy = 0.151 samples = 505 value = [494, 11] 28->29 30 entropy = 0.453 samples = 2371 value = [2146, 225] 28->30
In [140]:
system(dot -Tpng treefinal2.dot -o treefinal2.png)
Out[140]:
[]
In [141]:
from IPython.display import Image
Image(filename='treefinal2.png', width=800)
Out[141]:
In [142]:
#variables returned by decision tree
#'DBHVCLY_2.0','BMI','DBHVPAN_2.0','DBHVWLY_2.0','CANEV_2.0','ASISTLV_4.0','AHCNOYR2','BEDDAYR',
#'DBHVCLN_2.0','AMDLONGR_1.0','AHCNOYR2','FLA1AR_2'
In [143]:
#create new data frame

#health_cleaned
health_tree.tail()
Out[143]:
DBHVPAY_YES SEX_2 R_MARITL_2 R_MARITL_3 R_MARITL_4 MRACRPI2_2 MRACRPI2_3 MRACRPI2_4 REGION_2 REGION_3 ... ALCSTAT_9 ALCSTAT_10 YRSWRKPA ASISLEEP AHEIGHT BMI BEDDAYR CLCKTP AHCNOYR2 LOCALL1B
15908 0 1 1 0 0 0 0 0 0 0 ... 0 0 30.0 7.0 63.0 1984.0 30.0 3 8.0 4.0
15909 0 1 0 0 0 0 0 0 0 0 ... 0 0 1.0 8.0 66.0 2051.0 0.0 3 4.0 3.0
15910 1 1 1 0 0 0 0 0 0 1 ... 0 0 2.0 8.0 67.0 3601.0 1.0 3 2.0 4.0
15911 1 1 0 0 0 1 0 0 0 1 ... 0 0 18.0 7.0 64.0 3775.0 0.0 3 3.0 3.0
15912 0 1 0 0 0 0 0 0 0 1 ... 0 0 6.0 8.0 66.0 1858.0 2.0 4 4.0 6.0

5 rows × 143 columns

In [144]:
health_tree= pd.DataFrame(health_tree)
In [145]:
health_tree.head(1)
Out[145]:
DBHVPAY_YES SEX_2 R_MARITL_2 R_MARITL_3 R_MARITL_4 MRACRPI2_2 MRACRPI2_3 MRACRPI2_4 REGION_2 REGION_3 ... ALCSTAT_9 ALCSTAT_10 YRSWRKPA ASISLEEP AHEIGHT BMI BEDDAYR CLCKTP AHCNOYR2 LOCALL1B
0 1 1 1 0 0 0 0 0 0 1 ... 0 0 28.0 8.0 61.0 2930.0 0.0 4 2.0 5.0

1 rows × 143 columns

In [146]:
hn = health_tree[['DBHVPAY_YES','DBHVCLY_2.0','BMI','DBHVPAN_2.0','DBHVWLY_2.0','CANEV_2.0','ASISTLV_4.0','AHCNOYR2','BEDDAYR','DBHVCLN_2.0','AMDLONGR_1.0','AHCNOYR2','FLA1AR_2']]
hn.head()
Out[146]:
DBHVPAY_YES DBHVCLY_2.0 BMI DBHVPAN_2.0 DBHVWLY_2.0 CANEV_2.0 ASISTLV_4.0 AHCNOYR2 BEDDAYR DBHVCLN_2.0 AMDLONGR_1.0 AHCNOYR2 FLA1AR_2
0 1 1 2930.0 0 1 1 1 2.0 0.0 0 0 2.0 1
1 0 0 3544.0 0 1 1 0 0.0 4.0 0 1 0.0 0
2 1 1 4313.0 0 1 1 1 3.0 6.0 0 1 3.0 1
3 0 1 3227.0 0 1 1 0 2.0 0.0 1 0 2.0 1
4 0 1 2467.0 0 1 1 0 2.0 0.0 0 1 2.0 1
In [147]:
y = hn['DBHVPAY_YES'] # y variable
X = hn[['DBHVCLY_2.0','BMI','DBHVPAN_2.0','DBHVWLY_2.0','CANEV_2.0','ASISTLV_4.0','AHCNOYR2','BEDDAYR','DBHVCLN_2.0','AMDLONGR_1.0','AHCNOYR2','FLA1AR_2']]
X.head()
Out[147]:
DBHVCLY_2.0 BMI DBHVPAN_2.0 DBHVWLY_2.0 CANEV_2.0 ASISTLV_4.0 AHCNOYR2 AHCNOYR2 BEDDAYR DBHVCLN_2.0 AMDLONGR_1.0 AHCNOYR2 AHCNOYR2 FLA1AR_2
0 1 2930.0 0 1 1 1 2.0 2.0 0.0 0 0 2.0 2.0 1
1 0 3544.0 0 1 1 0 0.0 0.0 4.0 0 1 0.0 0.0 0
2 1 4313.0 0 1 1 1 3.0 3.0 6.0 0 1 3.0 3.0 1
3 1 3227.0 0 1 1 0 2.0 2.0 0.0 1 0 2.0 2.0 1
4 1 2467.0 0 1 1 0 2.0 2.0 0.0 0 1 2.0 2.0 1
In [148]:
#create train and test sets
from sklearn.cross_validation import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=9874)
print "X_train", X_train.shape
print "y_train", y_train.shape
print "X_test", X_test.shape
print "y_test", y_test.shape
X_train (12730, 14)
y_train (12730L,)
X_test (3183, 14)
y_test (3183L,)
In [149]:
##############################################################################################################

#Logistic Regression

##############################################################################################################
In [150]:
from sklearn.linear_model import LogisticRegression
In [151]:
#logistic regression with recursive feature elimination using cross validation
LogReg = LogisticRegression()
refcv = RFECV(LogReg, cv = 10, step = 1, n_jobs = -1)
fitcv = refcv.fit(X_train, y_train)
In [152]:
y_pred = fitcv.predict(X_test)
y_pred
Out[152]:
array([0, 0, 1, ..., 1, 0, 0], dtype=uint8)
In [153]:
from sklearn.metrics import confusion_matrix
confusion_matrix = confusion_matrix(y_test, y_pred)
confusion_matrix
Out[153]:
array([[1942,  186],
       [ 419,  636]], dtype=int64)
In [154]:
print(classification_report(y_test, y_pred))
             precision    recall  f1-score   support

          0       0.82      0.91      0.87      2128
          1       0.77      0.60      0.68      1055

avg / total       0.81      0.81      0.80      3183

In [155]:
#np.set_printoptions(threshold=np.inf)
np.set_printoptions(threshold=1000)
print "", y_pred
 [0 0 1 ... 1 0 0]
In [156]:
print("Accuracy:",metrics.accuracy_score(y_test, y_pred))
print("Precision:",metrics.precision_score(y_test, y_pred))
print("Recall:",metrics.recall_score(y_test, y_pred))
('Accuracy:', 0.8099277411247251)
('Precision:', 0.7737226277372263)
('Recall:', 0.6028436018957346)
In [157]:
y_pred_proba = fitcv.predict_proba(X_test)[::,1]
fpr, tpr, _ = metrics.roc_curve(y_test,  y_pred_proba)
auc = metrics.roc_auc_score(y_test, y_pred_proba)
plt.plot(fpr,tpr,label="auc="+str(auc))
plt.legend(loc=4)
plt.show()
print "Area Under Curve AUC is ", auc
Area Under Curve AUC is  0.8445279371414318
In [158]:
fitcv.score(X_train, y_train)
Out[158]:
0.8066771406127259
In [159]:
fitcv.score(X_test, y_test)
Out[159]:
0.8099277411247251
In [160]:
print("Num Features: %d") % fitcv.n_features_
Num Features: 14
In [161]:
print("Selected Features: %s") % fitcv.support_
Selected Features: [ True  True  True  True  True  True  True  True  True  True  True  True  True  True]
In [162]:
lr_selected = fitcv.support_
lr_selected
Out[162]:
array([ True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True,  True])
In [163]:
lr_rank = fitcv.ranking_
print("Feature Ranking: %s") % fitcv.ranking_
Feature Ranking: [1 1 1 1 1 1 1 1 1 1 1 1 1 1]
In [165]:
lr_cols = X_train.columns.values
lr_cols
Out[165]:
array(['DBHVCLY_2.0', 'BMI', 'DBHVPAN_2.0', 'DBHVWLY_2.0', 'CANEV_2.0', 'ASISTLV_4.0', 'AHCNOYR2', 'AHCNOYR2', 'BEDDAYR', 'DBHVCLN_2.0', 'AMDLONGR_1.0', 'AHCNOYR2', 'AHCNOYR2', 'FLA1AR_2'], dtype=object)
In [167]:
for i in range(len(lr_cols)):
    #if lr_selected[i]:
    print lr_cols[i],'\t', lr_rank[i] 
DBHVCLY_2.0 	1
BMI 	1
DBHVPAN_2.0 	1
DBHVWLY_2.0 	1
CANEV_2.0 	1
ASISTLV_4.0 	1
AHCNOYR2 	1
AHCNOYR2 	1
BEDDAYR 	1
DBHVCLN_2.0 	1
AMDLONGR_1.0 	1
AHCNOYR2 	1
AHCNOYR2 	1
FLA1AR_2 	1
In [168]:
#############################################################################################################

#logistic regression with cross validation using recursive feature elimination

#############################################################################################################
In [169]:
from sklearn.linear_model import LogisticRegressionCV
from sklearn.feature_selection import RFE
In [170]:
X_train.tail()
Out[170]:
DBHVCLY_2.0 BMI DBHVPAN_2.0 DBHVWLY_2.0 CANEV_2.0 ASISTLV_4.0 AHCNOYR2 AHCNOYR2 BEDDAYR DBHVCLN_2.0 AMDLONGR_1.0 AHCNOYR2 AHCNOYR2 FLA1AR_2
3537 1 2861.0 0 0 1 0 3.0 3.0 1.0 0 1 3.0 3.0 1
15043 1 2434.0 0 1 1 0 0.0 0.0 0.0 1 0 0.0 0.0 1
6536 0 2434.0 0 1 1 1 1.0 1.0 0.0 0 1 1.0 1.0 0
1778 0 5274.0 0 0 1 0 3.0 3.0 0.0 0 1 3.0 3.0 0
631 1 2240.0 0 1 0 0 8.0 8.0 0.0 0 1 8.0 8.0 0
In [171]:
LogRegCV = LogisticRegressionCV(cv=10, random_state=123231, multi_class='ovr')
In [172]:
rfe = RFE(LogRegCV,5)
In [173]:
fit = rfe.fit(X_train, y_train)
In [174]:
y_pred_cv = fit.predict(X_test)
y_pred_cv
Out[174]:
array([0, 0, 1, ..., 1, 0, 0], dtype=uint8)
In [175]:
from sklearn.metrics import confusion_matrix
confusion_matrix = confusion_matrix(y_test, y_pred_cv)
confusion_matrix
Out[175]:
array([[1942,  186],
       [ 434,  621]], dtype=int64)
In [176]:
lg = classification_report(y_test, y_pred_cv)
print lg
#print(classification_report(y_test, y_pred_cv))
             precision    recall  f1-score   support

          0       0.82      0.91      0.86      2128
          1       0.77      0.59      0.67      1055

avg / total       0.80      0.81      0.80      3183

In [177]:
import pylab as plt
%matplotlib inline
plt.matshow(confusion_matrix)
plt.title('Confusion matrix')
plt.colorbar()
plt.ylabel('Actual')
plt.xlabel('Predicted')
plt.show()
In [178]:
print("Accuracy:",metrics.accuracy_score(y_test, y_pred_cv))
print("Precision:",metrics.precision_score(y_test, y_pred_cv))
print("Recall:",metrics.recall_score(y_test, y_pred_cv))
('Accuracy:', 0.80521520578071)
('Precision:', 0.7695167286245354)
('Recall:', 0.5886255924170616)
In [179]:
y_pred_proba_cv = fit.predict_proba(X_test)[::,1]
fpr, tpr, _ = metrics.roc_curve(y_test,  y_pred_proba_cv)
auc = metrics.roc_auc_score(y_test, y_pred_proba_cv)
plt.plot(fpr,tpr,label="auc="+str(auc))
plt.legend(loc=4)
plt.show()
print "Area Under Curve AUC is ", auc
Area Under Curve AUC is  0.8323573299362148
In [180]:
fit.score(X_train, y_train)
Out[180]:
0.80471327572663
In [181]:
fit.score(X_test, y_test)
Out[181]:
0.80521520578071
In [182]:
print("Num Features: %d") % fit.n_features_
Num Features: 5
In [183]:
print("Selected Features: %s") % fit.support_
Selected Features: [ True False  True  True False False False False False False  True False False  True]
In [184]:
lr_selected = fit.support_
lr_selected
Out[184]:
array([ True, False,  True,  True, False, False, False, False, False, False,  True, False, False,  True])
In [185]:
lr_rank = fit.ranking_
print("Feature Ranking: %s") % fit.ranking_
Feature Ranking: [ 1 10  1  1  3  2  7  6  9  8  1  5  4  1]
In [186]:
lr_cols = X_train.columns.values
lr_cols
Out[186]:
array(['DBHVCLY_2.0', 'BMI', 'DBHVPAN_2.0', 'DBHVWLY_2.0', 'CANEV_2.0', 'ASISTLV_4.0', 'AHCNOYR2', 'AHCNOYR2', 'BEDDAYR', 'DBHVCLN_2.0', 'AMDLONGR_1.0', 'AHCNOYR2', 'AHCNOYR2', 'FLA1AR_2'], dtype=object)
In [187]:
for i in range(len(lr_cols)):
    #if lr_selected[i]:
    print lr_cols[i],'\t', lr_rank[i] 
DBHVCLY_2.0 	1
BMI 	10
DBHVPAN_2.0 	1
DBHVWLY_2.0 	1
CANEV_2.0 	3
ASISTLV_4.0 	2
AHCNOYR2 	7
AHCNOYR2 	6
BEDDAYR 	9
DBHVCLN_2.0 	8
AMDLONGR_1.0 	1
AHCNOYR2 	5
AHCNOYR2 	4
FLA1AR_2 	1
In [188]:
# varaibles selected: DBHVCLY_2.0, DBHVPAN_2.0, DBHVWLY_2.0, AMDLONGR_1.0, FLA1AR_2
In [189]:
###############################################################################################

# Logistic Regression using stasmodels.org api

#################################################################################################
In [190]:
import statsmodels.api as sm
In [191]:
hn.head()
Out[191]:
DBHVPAY_YES DBHVCLY_2.0 BMI DBHVPAN_2.0 DBHVWLY_2.0 CANEV_2.0 ASISTLV_4.0 AHCNOYR2 BEDDAYR DBHVCLN_2.0 AMDLONGR_1.0 AHCNOYR2 FLA1AR_2
0 1 1 2930.0 0 1 1 1 2.0 0.0 0 0 2.0 1
1 0 0 3544.0 0 1 1 0 0.0 4.0 0 1 0.0 0
2 1 1 4313.0 0 1 1 1 3.0 6.0 0 1 3.0 1
3 0 1 3227.0 0 1 1 0 2.0 0.0 1 0 2.0 1
4 0 1 2467.0 0 1 1 0 2.0 0.0 0 1 2.0 1
In [192]:
ys = health_tree_drop['DBHVPAY_YES'] # y variable
Xs = health_tree_drop[health_names[1:]]
In [193]:
ys.tail()
Out[193]:
15908    0
15909    0
15910    1
15911    1
15912    0
Name: DBHVPAY_YES, dtype: uint8
In [194]:
Xs.dtypes
Out[194]:
SEX_2             uint8
R_MARITL_2        uint8
R_MARITL_3        uint8
R_MARITL_4        uint8
MRACRPI2_2        uint8
MRACRPI2_3        uint8
MRACRPI2_4        uint8
REGION_2          uint8
REGION_3          uint8
REGION_4          uint8
PAR_STAT_2        uint8
PAR_STAT_3        uint8
DOINGLWA_2.0      uint8
DOINGLWA_3.0      uint8
DOINGLWA_4.0      uint8
DOINGLWA_5.0      uint8
SUPERVIS_2.0      uint8
WRKCATA_2.0       uint8
WRKCATA_3.0       uint8
WRKCATA_4.0       uint8
WRKCATA_5.0       uint8
WRKCATA_6.0       uint8
HOURPDA_2.0       uint8
PDSICKA_2.0       uint8
WRKLYR4_1.0       uint8
WRKLYR4_2.0       uint8
HYPEV_2.0         uint8
HYBPLEV_2.0       uint8
HYBPLEV_3.0       uint8
HYBPLEV_4.0       uint8
                 ...   
ASIRETR_2.0       uint8
ASIRETR_3.0       uint8
ASIRETR_4.0       uint8
ASIMEDC_2.0       uint8
ASIMEDC_3.0       uint8
ASIMEDC_4.0       uint8
ASISTLV_2.0       uint8
ASISTLV_3.0       uint8
ASISTLV_4.0       uint8
ASICNHC_2.0       uint8
ASICNHC_3.0       uint8
ASICNHC_4.0       uint8
AWEBUSE_2.0       uint8
YTQU_YG1_2.0      uint8
ALCSTAT_2         uint8
ALCSTAT_3         uint8
ALCSTAT_5         uint8
ALCSTAT_6         uint8
ALCSTAT_7         uint8
ALCSTAT_8         uint8
ALCSTAT_9         uint8
ALCSTAT_10        uint8
YRSWRKPA        float64
ASISLEEP        float64
AHEIGHT         float64
BMI             float64
BEDDAYR         float64
CLCKTP            int64
AHCNOYR2        float64
LOCALL1B        float64
Length: 142, dtype: object
In [195]:
Xs.dtypes
Out[195]:
SEX_2             uint8
R_MARITL_2        uint8
R_MARITL_3        uint8
R_MARITL_4        uint8
MRACRPI2_2        uint8
MRACRPI2_3        uint8
MRACRPI2_4        uint8
REGION_2          uint8
REGION_3          uint8
REGION_4          uint8
PAR_STAT_2        uint8
PAR_STAT_3        uint8
DOINGLWA_2.0      uint8
DOINGLWA_3.0      uint8
DOINGLWA_4.0      uint8
DOINGLWA_5.0      uint8
SUPERVIS_2.0      uint8
WRKCATA_2.0       uint8
WRKCATA_3.0       uint8
WRKCATA_4.0       uint8
WRKCATA_5.0       uint8
WRKCATA_6.0       uint8
HOURPDA_2.0       uint8
PDSICKA_2.0       uint8
WRKLYR4_1.0       uint8
WRKLYR4_2.0       uint8
HYPEV_2.0         uint8
HYBPLEV_2.0       uint8
HYBPLEV_3.0       uint8
HYBPLEV_4.0       uint8
                 ...   
ASIRETR_2.0       uint8
ASIRETR_3.0       uint8
ASIRETR_4.0       uint8
ASIMEDC_2.0       uint8
ASIMEDC_3.0       uint8
ASIMEDC_4.0       uint8
ASISTLV_2.0       uint8
ASISTLV_3.0       uint8
ASISTLV_4.0       uint8
ASICNHC_2.0       uint8
ASICNHC_3.0       uint8
ASICNHC_4.0       uint8
AWEBUSE_2.0       uint8
YTQU_YG1_2.0      uint8
ALCSTAT_2         uint8
ALCSTAT_3         uint8
ALCSTAT_5         uint8
ALCSTAT_6         uint8
ALCSTAT_7         uint8
ALCSTAT_8         uint8
ALCSTAT_9         uint8
ALCSTAT_10        uint8
YRSWRKPA        float64
ASISLEEP        float64
AHEIGHT         float64
BMI             float64
BEDDAYR         float64
CLCKTP            int64
AHCNOYR2        float64
LOCALL1B        float64
Length: 142, dtype: object
In [196]:
logit_model=sm.Logit(ys,Xs)
result=logit_model.fit()
print(result.summary2())
C:\Users\lenovo\Anaconda2\lib\site-packages\statsmodels\discrete\discrete_model.py:1674: RuntimeWarning: overflow encountered in exp
  return 1/(1+np.exp(-X))
C:\Users\lenovo\Anaconda2\lib\site-packages\statsmodels\discrete\discrete_model.py:1724: RuntimeWarning: divide by zero encountered in log
  return np.sum(np.log(self.cdf(q*np.dot(X,params))))
Optimization terminated successfully.
         Current function value: inf
         Iterations 7
C:\Users\lenovo\Anaconda2\lib\site-packages\statsmodels\base\model.py:488: HessianInversionWarning: Inverting hessian failed, no bse or cov_params available
  'available', HessianInversionWarning)
C:\Users\lenovo\Anaconda2\lib\site-packages\statsmodels\base\model.py:488: HessianInversionWarning: Inverting hessian failed, no bse or cov_params available
  'available', HessianInversionWarning)
                               Results: Logit
============================================================================
Model:                   Logit                 Pseudo R-squared:      inf   
Dependent Variable:      DBHVPAY_YES           AIC:                   inf   
Date:                    2018-11-19 22:52      BIC:                   inf   
No. Observations:        15913                 Log-Likelihood:        -inf  
Df Model:                140                   LL-Null:               0.0000
Df Residuals:            15772                 LLR p-value:           1.0000
Converged:               1.0000                Scale:                 1.0000
No. Iterations:          7.0000                                             
----------------------------------------------------------------------------
              Coef.    Std.Err.      z     P>|z|      [0.025       0.975]   
----------------------------------------------------------------------------
SEX_2         0.2126       0.0658   3.2303 0.0012        0.0836       0.3415
R_MARITL_2   -0.1097       0.0834  -1.3152 0.1884       -0.2732       0.0538
R_MARITL_3   -0.1109       0.0627  -1.7698 0.0768       -0.2338       0.0119
R_MARITL_4   -0.0479       0.0604  -0.7935 0.4275       -0.1662       0.0704
MRACRPI2_2    0.0580       0.0780   0.7438 0.4570       -0.0949       0.2109
MRACRPI2_3    0.0799       0.2052   0.3892 0.6971       -0.3224       0.4821
MRACRPI2_4    0.6256       0.0970   6.4523 0.0000        0.4355       0.8156
REGION_2      0.0305       0.0703   0.4335 0.6646       -0.1073       0.1682
REGION_3      0.0828       0.0657   1.2607 0.2074       -0.0459       0.2116
REGION_4      0.1338       0.0705   1.8966 0.0579       -0.0045       0.2720
PAR_STAT_2    0.0067       0.1399   0.0482 0.9615       -0.2674       0.2809
PAR_STAT_3    0.0999       0.0584   1.7089 0.0875       -0.0147       0.2144
DOINGLWA_2.0  0.0574       0.1387   0.4140 0.6789       -0.2144       0.3293
DOINGLWA_3.0 -0.0074 2269652.2361  -0.0000 1.0000 -4448436.6475 4448436.6328
DOINGLWA_4.0 -0.0818       0.2640  -0.3099 0.7566       -0.5994       0.4357
DOINGLWA_5.0 -0.0588 2269652.2361  -0.0000 1.0000 -4448436.6990 4448436.5813
SUPERVIS_2.0  0.0145       0.0475   0.3047 0.7606       -0.0786       0.1076
WRKCATA_2.0  -0.2771       0.1136  -2.4392 0.0147       -0.4997      -0.0544
WRKCATA_3.0   0.0339       0.0795   0.4257 0.6704       -0.1220       0.1897
WRKCATA_4.0   0.1160       0.0828   1.4007 0.1613       -0.0463       0.2783
WRKCATA_5.0  -0.2395       0.0947  -2.5296 0.0114       -0.4251      -0.0539
WRKCATA_6.0   0.0301       0.4020   0.0749 0.9403       -0.7577       0.8180
HOURPDA_2.0   0.2148       0.0490   4.3871 0.0000        0.1188       0.3108
PDSICKA_2.0  -0.1608       0.0532  -3.0239 0.0025       -0.2651      -0.0566
WRKLYR4_1.0  -0.0448 2269652.2361  -0.0000 1.0000 -4448436.6850 4448436.5953
WRKLYR4_2.0  -0.0213 2269652.2361  -0.0000 1.0000 -4448436.6615 4448436.6188
HYPEV_2.0    -0.2675       0.0535  -4.9970 0.0000       -0.3724      -0.1626
HYBPLEV_2.0   0.3818       0.2524   1.5129 0.1303       -0.1128       0.8764
HYBPLEV_3.0   0.2955       0.2444   1.2093 0.2266       -0.1834       0.7744
HYBPLEV_4.0   0.2334       0.2641   0.8836 0.3769       -0.2843       0.7510
HYBPLEV_5.0   0.7915       0.2814   2.8128 0.0049        0.2400       1.3431
CHLEV_2.0    -0.2075       0.0498  -4.1670 0.0000       -0.3051      -0.1099
CHDEV_2.0     0.0697       0.1156   0.6031 0.5465       -0.1569       0.2964
MIEV_2.0     -0.2224       0.1352  -1.6452 0.0999       -0.4873       0.0425
STREV_2.0    -0.1404       0.1211  -1.1592 0.2464       -0.3778       0.0970
COPDEV_2.0   -0.0909       0.1154  -0.7872 0.4311       -0.3171       0.1354
AASMEV_2.0   -0.0452       0.0634  -0.7134 0.4756       -0.1694       0.0790
ULCEV_2.0     0.0414       0.0840   0.4927 0.6222       -0.1232       0.2060
CANEV_2.0     0.1580       0.0673   2.3468 0.0189        0.0261       0.2900
DBHVCLY_2.0  -2.1932       0.0534 -41.0639 0.0000       -2.2978      -2.0885
DBHVWLY_2.0  -1.0299       0.1048  -9.8307 0.0000       -1.2353      -0.8246
DBHVPAN_2.0  -0.7763       0.0495 -15.6709 0.0000       -0.8734      -0.6792
DBHVCLN_2.0   0.2014       0.0499   4.0361 0.0001        0.1036       0.2991
DBHVWLN_2.0   0.1838       0.0867   2.1216 0.0339        0.0140       0.3537
DIBREL_2.0   -0.1142       0.0459  -2.4882 0.0128       -0.2041      -0.0242
DIBEV1_3.0   -0.1004       0.1408  -0.7130 0.4759       -0.3763       0.1755
DIBPRE2_2.0  -0.3364       0.0875  -3.8441 0.0001       -0.5079      -0.1649
EPILEP1_2.0  -0.0339       0.1542  -0.2198 0.8260       -0.3361       0.2683
AHAYFYR_2.0  -0.1042       0.0752  -1.3855 0.1659       -0.2515       0.0432
SINYR_2.0    -0.0419       0.0640  -0.6546 0.5127       -0.1673       0.0835
CBRCHYR_2.0   0.1542       0.1183   1.3034 0.1924       -0.0777       0.3861
KIDWKYR_2.0  -0.1405       0.1571  -0.8943 0.3712       -0.4484       0.1674
LIVYR_2.0    -0.3153       0.1961  -1.6076 0.1079       -0.6997       0.0691
JNTSYMP_2.0  -0.0896       0.0537  -1.6688 0.0952       -0.1948       0.0156
ARTH1_2.0     0.0015       0.0576   0.0265 0.9788       -0.1113       0.1144
PAINECK_2.0  -0.0990       0.0644  -1.5372 0.1242       -0.2253       0.0272
PAINLB_2.0   -0.0951       0.0537  -1.7727 0.0763       -0.2003       0.0100
PAINFACE_2.0 -0.1501       0.1035  -1.4499 0.1471       -0.3530       0.0528
AMIGR_2.0    -0.0648       0.0652  -0.9933 0.3206       -0.1927       0.0631
ACOLD2W_2.0   0.0870       0.0679   1.2801 0.2005       -0.0462       0.2201
AINTIL2W_2.0 -0.1380       0.1021  -1.3510 0.1767       -0.3382       0.0622
AHEARST1_2.0  0.1589       0.0499   3.1821 0.0015        0.0610       0.2568
AHEARST1_3.0  0.0951       0.0752   1.2642 0.2061       -0.0523       0.2425
AHEARST1_4.0  0.3272       0.1080   3.0287 0.0025        0.1154       0.5389
AHEARST1_5.0  0.2733       0.1507   1.8138 0.0697       -0.0220       0.5687
AHEARST1_6.0  0.8940       0.4196   2.1307 0.0331        0.0716       1.7163
AVISION_2.0  -0.0665       0.0725  -0.9173 0.3590       -0.2087       0.0756
VIM_GLEV_2.0 -0.0374       0.1259  -0.2973 0.7663       -0.2842       0.2094
VIM_MDEV_2.0 -0.0352       0.1330  -0.2650 0.7910       -0.2959       0.2254
VIMGLASS_2.0 -0.1302       0.0520  -2.5009 0.0124       -0.2322      -0.0282
AVISACT_2.0   0.2998       0.0543   5.5239 0.0000        0.1934       0.4062
CHPAIN6M_2.0  0.0685       0.0548   1.2508 0.2110       -0.0388       0.1758
CHPAIN6M_3.0 -0.0448       0.0942  -0.4756 0.6344       -0.2294       0.1398
CHPAIN6M_4.0 -0.0458       0.0901  -0.5089 0.6109       -0.2224       0.1307
AHSTATYR_2.0 -0.1302       0.0932  -1.3972 0.1624       -0.3130       0.0525
AHSTATYR_3.0 -0.0422       0.0556  -0.7587 0.4480       -0.1511       0.0668
FLA1AR_2     -0.3052       0.0566  -5.3915 0.0000       -0.4162      -0.1943
FLA1AR_3      0.5730       1.4977   0.3826 0.7021       -2.3625       3.5084
SPECEQ_2.0   -0.1115       0.0896  -1.2445 0.2133       -0.2872       0.0641
ALC1YR_2.0    0.0279       0.1207   0.2313 0.8171       -0.2087       0.2646
CIGAREV2_2.0 -0.0528       0.0555  -0.9511 0.3416       -0.1615       0.0560
ECIGEV2_2.0  -0.0117       0.0741  -0.1580 0.8744       -0.1570       0.1336
SMKSTAT2_2.0 -0.1275       0.1391  -0.9161 0.3596       -0.4002       0.1452
SMKSTAT2_3.0 -0.0337       0.0863  -0.3906 0.6961       -0.2028       0.1354
SMKSTAT2_4.0 -0.0646       0.0859  -0.7522 0.4519       -0.2331       0.1038
APLKIND_2.0   0.0521       0.0534   0.9749 0.3296       -0.0526       0.1568
APLKIND_3.0  -0.2554       0.2468  -1.0346 0.3009       -0.7392       0.2284
APLKIND_4.0   0.2243       0.1978   1.1337 0.2569       -0.1634       0.6120
APLKIND_5.0  -0.7672       0.2313  -3.3164 0.0009       -1.2206      -0.3138
APLKIND_6.0  -0.1194       0.3544  -0.3370 0.7361       -0.8140       0.5751
AWORPAY_2.0   0.0180       0.0900   0.2001 0.8414       -0.1584       0.1944
AWORPAY_3.0   0.0090       0.0955   0.0942 0.9249       -0.1781       0.1961
ADNLONG2_1.0 -0.1817       0.3502  -0.5189 0.6038       -0.8682       0.5047
ADNLONG2_2.0 -0.1235       0.3521  -0.3507 0.7258       -0.8135       0.5666
ADNLONG2_3.0 -0.1076       0.3537  -0.3044 0.7609       -0.8008       0.5855
ADNLONG2_4.0 -0.1079       0.3545  -0.3043 0.7609       -0.8027       0.5870
ADNLONG2_5.0 -0.0876       0.3556  -0.2464 0.8054       -0.7845       0.6093
ASRGYR_2.0    0.0489       0.0626   0.7818 0.4344       -0.0738       0.1716
AMDLONGR_1.0  0.2506       0.2965   0.8454 0.3979       -0.3305       0.8317
AMDLONGR_2.0  0.1040       0.3010   0.3455 0.7297       -0.4860       0.6940
AMDLONGR_3.0 -0.4908       0.3188  -1.5396 0.1237       -1.1157       0.1340
AMDLONGR_4.0 -0.9645       0.3698  -2.6084 0.0091       -1.6892      -0.2398
AMDLONGR_5.0 -1.2833       0.5528  -2.3214 0.0203       -2.3668      -0.1998
HIT1A_2.0    -0.1345       0.0541  -2.4874 0.0129       -0.2405      -0.0285
HIT2A_2.0     0.0019       0.0698   0.0271 0.9784       -0.1349       0.1386
HIT3A_2.0    -0.0105       0.0687  -0.1527 0.8786       -0.1451       0.1242
HIT4A_2.0    -0.2070       0.0651  -3.1813 0.0015       -0.3346      -0.0795
FLUVACYR_2.0 -0.0647       0.0463  -1.3989 0.1618       -0.1554       0.0260
LIVEV_2.0     0.2581       0.2294   1.1249 0.2606       -0.1916       0.7078
ASICPUSE_2.0  0.3288       0.1116   2.9448 0.0032        0.1099       0.5476
ASICPUSE_3.0  0.1988       0.1303   1.5253 0.1272       -0.0567       0.4543
ASICPUSE_4.0  0.3602       0.1082   3.3308 0.0009        0.1483       0.5722
ASIRETR_2.0  -0.0573       0.0846  -0.6775 0.4981       -0.2231       0.1085
ASIRETR_3.0  -0.0536       0.0952  -0.5632 0.5733       -0.2403       0.1330
ASIRETR_4.0  -0.0983       0.1025  -0.9594 0.3374       -0.2992       0.1025
ASIMEDC_2.0   0.1974       0.0929   2.1238 0.0337        0.0152       0.3795
ASIMEDC_3.0   0.0156       0.1044   0.1494 0.8812       -0.1891       0.2203
ASIMEDC_4.0  -0.0695       0.1125  -0.6181 0.5365       -0.2900       0.1509
ASISTLV_2.0  -0.0602       0.1012  -0.5949 0.5519       -0.2585       0.1381
ASISTLV_3.0  -0.1568       0.1112  -1.4104 0.1584       -0.3747       0.0611
ASISTLV_4.0  -0.3137       0.1200  -2.6143 0.0089       -0.5489      -0.0785
ASICNHC_2.0   0.0727       0.1111   0.6548 0.5126       -0.1450       0.2904
ASICNHC_3.0   0.0738       0.1164   0.6338 0.5262       -0.1544       0.3019
ASICNHC_4.0   0.1915       0.1190   1.6097 0.1075       -0.0417       0.4247
AWEBUSE_2.0   0.2438       0.1023   2.3827 0.0172        0.0433       0.4443
YTQU_YG1_2.0  0.2289       0.0644   3.5555 0.0004        0.1027       0.3551
ALCSTAT_2     0.1219       0.0971   1.2557 0.2092       -0.0684       0.3122
ALCSTAT_3     0.0269       0.1611   0.1670 0.8674       -0.2888       0.3426
ALCSTAT_5    -0.0268       0.1011  -0.2649 0.7910       -0.2249       0.1714
ALCSTAT_6     0.0697       0.1394   0.5003 0.6169       -0.2035       0.3430
ALCSTAT_7    -0.0161       0.1448  -0.1115 0.9112       -0.2999       0.2676
ALCSTAT_8     0.1040       0.1607   0.6471 0.5176       -0.2110       0.4191
ALCSTAT_9    -0.6241       0.5854  -1.0661 0.2864       -1.7715       0.5233
ALCSTAT_10   -0.2438       0.3676  -0.6633 0.5071       -0.9643       0.4766
YRSWRKPA      0.0006       0.0025   0.2527 0.8005       -0.0043       0.0055
ASISLEEP      0.0336       0.0170   1.9758 0.0482        0.0003       0.0669
AHEIGHT       0.0101       0.0067   1.5114 0.1307       -0.0030       0.0233
BMI           0.0006       0.0000  13.4446 0.0000        0.0005       0.0007
BEDDAYR       0.0015       0.0009   1.7285 0.0839       -0.0002       0.0032
CLCKTP        0.0010       0.0157   0.0656 0.9477       -0.0297       0.0318
AHCNOYR2      0.0608       0.0123   4.9657 0.0000        0.0368       0.0848
LOCALL1B     -0.0076       0.0097  -0.7905 0.4293       -0.0266       0.0113
============================================================================

In [197]:
cols=['SEX_2',	'MRACRPI2_4',	'WRKCATA_2.0',	'WRKCATA_5.0',	'HOURPDA_2.0',	'PDSICKA_2.0',	'HYPEV_2.0',	'HYBPLEV_5.0',	'CHLEV_2.0',	'CANEV_2.0',	'DBHVCLY_2.0',	'DBHVWLY_2.0',	'DBHVPAN_2.0',	'DBHVCLN_2.0',	'DBHVWLN_2.0',	'DIBREL_2.0',	'DIBPRE2_2.0',	'AHEARST1_2.0',	'AHEARST1_4.0',	'AHEARST1_6.0',	'VIMGLASS_2.0',	'AVISACT_2.0',	'FLA1AR_2',	'APLKIND_5.0',	'AMDLONGR_4.0',	'AMDLONGR_5.0',	'HIT1A_2.0',	'HIT4A_2.0',	'ASICPUSE_2.0',	'ASICPUSE_4.0',	'ASIMEDC_2.0',	'ASISTLV_4.0',	'AWEBUSE_2.0',	'YTQU_YG1_2.0',	'ASISLEEP',	'BMI',	'AHCNOYR2']
cols[0:5]
Out[197]:
['SEX_2', 'MRACRPI2_4', 'WRKCATA_2.0', 'WRKCATA_5.0', 'HOURPDA_2.0']
In [198]:
Xs2= health_tree_drop[cols]
Xs2[0:5]
Out[198]:
SEX_2 MRACRPI2_4 WRKCATA_2.0 WRKCATA_5.0 HOURPDA_2.0 PDSICKA_2.0 HYPEV_2.0 HYBPLEV_5.0 CHLEV_2.0 CANEV_2.0 ... HIT4A_2.0 ASICPUSE_2.0 ASICPUSE_4.0 ASIMEDC_2.0 ASISTLV_4.0 AWEBUSE_2.0 YTQU_YG1_2.0 ASISLEEP BMI AHCNOYR2
0 1 0 0 0 0 1 0 0 0 1 ... 1 0 1 0 1 0 1 8.0 2930.0 2.0
1 0 0 0 0 0 0 1 0 1 1 ... 1 0 0 1 0 0 1 5.0 3544.0 0.0
2 1 0 0 0 0 0 1 0 1 1 ... 1 0 1 0 1 0 0 8.0 4313.0 3.0
3 0 0 0 0 0 0 1 0 1 1 ... 1 0 1 0 0 0 0 8.0 3227.0 2.0
4 1 0 0 1 1 1 1 0 0 1 ... 1 1 0 0 0 0 1 7.0 2467.0 2.0

5 rows × 37 columns

In [199]:
ys2= ys
ys2.head()
Out[199]:
0    1
1    0
2    1
3    0
4    0
Name: DBHVPAY_YES, dtype: uint8
In [200]:
logit_model2=sm.Logit(ys2,Xs2)
result2=logit_model2.fit()
print(result2.summary2())
Optimization terminated successfully.
         Current function value: inf
         Iterations 7
C:\Users\lenovo\Anaconda2\lib\site-packages\statsmodels\base\model.py:488: HessianInversionWarning: Inverting hessian failed, no bse or cov_params available
  'available', HessianInversionWarning)
C:\Users\lenovo\Anaconda2\lib\site-packages\statsmodels\base\model.py:488: HessianInversionWarning: Inverting hessian failed, no bse or cov_params available
  'available', HessianInversionWarning)
                       Results: Logit
=============================================================
Model:              Logit            Pseudo R-squared: inf   
Dependent Variable: DBHVPAY_YES      AIC:              inf   
Date:               2018-11-19 22:52 BIC:              inf   
No. Observations:   15913            Log-Likelihood:   -inf  
Df Model:           36               LL-Null:          0.0000
Df Residuals:       15876            LLR p-value:      1.0000
Converged:          1.0000           Scale:            1.0000
No. Iterations:     7.0000                                   
-------------------------------------------------------------
              Coef.  Std.Err.    z     P>|z|   [0.025  0.975]
-------------------------------------------------------------
SEX_2         0.1426   0.0476   2.9957 0.0027  0.0493  0.2360
MRACRPI2_4    0.5928   0.0921   6.4353 0.0000  0.4122  0.7733
WRKCATA_2.0  -0.2586   0.1106  -2.3386 0.0194 -0.4752 -0.0419
WRKCATA_5.0  -0.2313   0.0878  -2.6348 0.0084 -0.4033 -0.0592
HOURPDA_2.0   0.2143   0.0459   4.6726 0.0000  0.1244  0.3043
PDSICKA_2.0  -0.1553   0.0486  -3.1996 0.0014 -0.2505 -0.0602
HYPEV_2.0    -0.3228   0.0482  -6.7006 0.0000 -0.4172 -0.2284
HYBPLEV_5.0   0.4692   0.1426   3.2905 0.0010  0.1897  0.7487
CHLEV_2.0    -0.2340   0.0478  -4.8934 0.0000 -0.3277 -0.1403
CANEV_2.0     0.1573   0.0643   2.4450 0.0145  0.0312  0.2834
DBHVCLY_2.0  -2.2037   0.0524 -42.0296 0.0000 -2.3064 -2.1009
DBHVWLY_2.0  -1.0073   0.0988 -10.1991 0.0000 -1.2009 -0.8137
DBHVPAN_2.0  -0.7673   0.0487 -15.7697 0.0000 -0.8626 -0.6719
DBHVCLN_2.0   0.1892   0.0492   3.8479 0.0001  0.0928  0.2855
DBHVWLN_2.0   0.1701   0.0837   2.0309 0.0423  0.0059  0.3342
DIBREL_2.0   -0.1270   0.0450  -2.8227 0.0048 -0.2153 -0.0388
DIBPRE2_2.0  -0.3260   0.0706  -4.6195 0.0000 -0.4643 -0.1877
AHEARST1_2.0  0.1389   0.0449   3.0944 0.0020  0.0509  0.2268
AHEARST1_4.0  0.3072   0.1020   3.0107 0.0026  0.1072  0.5073
AHEARST1_6.0  0.8787   0.4135   2.1249 0.0336  0.0682  1.6891
VIMGLASS_2.0 -0.1661   0.0500  -3.3200 0.0009 -0.2642 -0.0681
AVISACT_2.0   0.3046   0.0523   5.8223 0.0000  0.2021  0.4072
FLA1AR_2     -0.4191   0.0480  -8.7321 0.0000 -0.5132 -0.3250
APLKIND_5.0  -0.7298   0.2222  -3.2837 0.0010 -1.1653 -0.2942
AMDLONGR_4.0 -1.0822   0.2259  -4.7913 0.0000 -1.5249 -0.6395
AMDLONGR_5.0 -1.3555   0.4590  -2.9530 0.0031 -2.2551 -0.4558
HIT1A_2.0    -0.1654   0.0525  -3.1518 0.0016 -0.2682 -0.0625
HIT4A_2.0    -0.2363   0.0573  -4.1268 0.0000 -0.3486 -0.1241
ASICPUSE_2.0  0.2521   0.0872   2.8907 0.0038  0.0812  0.4230
ASICPUSE_4.0  0.2588   0.0699   3.7014 0.0002  0.1218  0.3959
ASIMEDC_2.0   0.2205   0.0510   4.3265 0.0000  0.1206  0.3204
ASISTLV_4.0  -0.2352   0.0479  -4.9058 0.0000 -0.3291 -0.1412
AWEBUSE_2.0   0.1938   0.0802   2.4160 0.0157  0.0366  0.3510
YTQU_YG1_2.0  0.2135   0.0619   3.4489 0.0006  0.0922  0.3349
ASISLEEP      0.0322   0.0148   2.1674 0.0302  0.0031  0.0613
BMI           0.0006   0.0000  16.7943 0.0000  0.0005  0.0007
AHCNOYR2      0.0986   0.0104   9.4971 0.0000  0.0783  0.1190
=============================================================

In [201]:
#crate test train
X_train2, X_test2, y_train2, y_test2 = train_test_split(Xs2, ys2, test_size=0.2, random_state=2323)
LogReg3 = LogisticRegression()
LogReg3.fit(X_train2, y_train2)
Out[201]:
LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,
          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,
          penalty='l2', random_state=None, solver='liblinear', tol=0.0001,
          verbose=0, warm_start=False)
In [202]:
#predict y
y_pred2 = LogReg3.predict(X_test2)
print('Accuracy : {:.2f}'.format(LogReg3.score(X_test2, y_test2)))
Accuracy : 0.81
In [203]:
#conf matrix
from sklearn.metrics import confusion_matrix
confusion_matrix3 = confusion_matrix(y_test2, y_pred2)
print(confusion_matrix3)
[[1949  206]
 [ 383  645]]
In [204]:
lg2 = classification_report(y_test2, y_pred2)
print lg2
             precision    recall  f1-score   support

          0       0.84      0.90      0.87      2155
          1       0.76      0.63      0.69      1028

avg / total       0.81      0.81      0.81      3183

In [205]:
y_pred_proba2 = LogReg3.predict_proba(X_test2)[::,1]
fpr, tpr, _ = metrics.roc_curve(y_test2,  y_pred_proba2)
auc = metrics.roc_auc_score(y_test2, y_pred_proba2)
plt.plot(fpr,tpr,label="auc="+str(auc))
plt.legend(loc=4)
plt.show()
print "Area Under Curve AUC is ", auc
Area Under Curve AUC is  0.8539312250038369
In [206]:
##############################################################################################################

#LDA

##############################################################################################################
In [207]:
ldclf = LinearDiscriminantAnalysis()
ldclf = ldclf.fit(X_train, y_train)
print "Score on Training: ", ldclf.score(X_train, y_train)
print "Score on Test: ", ldclf.score(X_test, y_test)
Score on Training:  0.806598586017282
Score on Test:  0.8080427269871191
C:\Users\lenovo\Anaconda2\lib\site-packages\sklearn\discriminant_analysis.py:388: UserWarning: Variables are collinear.
  warnings.warn("Variables are collinear.")
In [208]:
# 10-fold cross validation
cv_scores = cross_validation.cross_val_score(ldclf, X, y, cv=5)
cv_scores
C:\Users\lenovo\Anaconda2\lib\site-packages\sklearn\discriminant_analysis.py:388: UserWarning: Variables are collinear.
  warnings.warn("Variables are collinear.")
C:\Users\lenovo\Anaconda2\lib\site-packages\sklearn\discriminant_analysis.py:388: UserWarning: Variables are collinear.
  warnings.warn("Variables are collinear.")
C:\Users\lenovo\Anaconda2\lib\site-packages\sklearn\discriminant_analysis.py:388: UserWarning: Variables are collinear.
  warnings.warn("Variables are collinear.")
C:\Users\lenovo\Anaconda2\lib\site-packages\sklearn\discriminant_analysis.py:388: UserWarning: Variables are collinear.
  warnings.warn("Variables are collinear.")
C:\Users\lenovo\Anaconda2\lib\site-packages\sklearn\discriminant_analysis.py:388: UserWarning: Variables are collinear.
  warnings.warn("Variables are collinear.")
Out[208]:
array([0.81, 0.81, 0.79, 0.82, 0.8 ])
In [209]:
print("Overall Accuracy: %0.2f (+/- %0.2f)" % (cv_scores.mean(), cv_scores.std() * 2))
Overall Accuracy: 0.81 (+/- 0.02)
In [222]:
##############################################################################################################

#Clustering numerical variables

##############################################################################################################
In [223]:
health_cl = health_tree
print health_cl.shape
health_cl.tail()
(15913, 143)
Out[223]:
DBHVPAY_YES SEX_2 R_MARITL_2 R_MARITL_3 R_MARITL_4 MRACRPI2_2 MRACRPI2_3 MRACRPI2_4 REGION_2 REGION_3 ... ALCSTAT_9 ALCSTAT_10 YRSWRKPA ASISLEEP AHEIGHT BMI BEDDAYR CLCKTP AHCNOYR2 LOCALL1B
15908 0 1 1 0 0 0 0 0 0 0 ... 0 0 30.0 7.0 63.0 1984.0 30.0 3 8.0 4.0
15909 0 1 0 0 0 0 0 0 0 0 ... 0 0 1.0 8.0 66.0 2051.0 0.0 3 4.0 3.0
15910 1 1 1 0 0 0 0 0 0 1 ... 0 0 2.0 8.0 67.0 3601.0 1.0 3 2.0 4.0
15911 1 1 0 0 0 1 0 0 0 1 ... 0 0 18.0 7.0 64.0 3775.0 0.0 3 3.0 3.0
15912 0 1 0 0 0 0 0 0 0 1 ... 0 0 6.0 8.0 66.0 1858.0 2.0 4 4.0 6.0

5 rows × 143 columns

In [224]:
health_cl_num = health_cl[['YRSWRKPA','ASISLEEP','AHEIGHT','BMI','BEDDAYR','CLCKTP','AHCNOYR2','LOCALL1B']]
health_cl_num.tail()
Out[224]:
YRSWRKPA ASISLEEP AHEIGHT BMI BEDDAYR CLCKTP AHCNOYR2 LOCALL1B
15908 30.0 7.0 63.0 1984.0 30.0 3 8.0 4.0
15909 1.0 8.0 66.0 2051.0 0.0 3 4.0 3.0
15910 2.0 8.0 67.0 3601.0 1.0 3 2.0 4.0
15911 18.0 7.0 64.0 3775.0 0.0 3 3.0 3.0
15912 6.0 8.0 66.0 1858.0 2.0 4 4.0 6.0
In [225]:
#min max normalization of numerical variables
x = health_cl_num.values #returns a numpy array
min_max_scaler = preprocessing.MinMaxScaler()
x_scaled = min_max_scaler.fit_transform(x)
health_cl_num_norm = pd.DataFrame(x_scaled, columns=health_cl_num.columns)
health_cl_num_norm.columns = ['YRSWRKPA_NORM','ASISLEEP_NORM','AHEIGHT_NORM','BMI_NORM','BEDDAYR_NORM','CLCKTP_NORM','AHCNOYR2_NORM','LOCALL1B_NORM']

health_cl_num_norm.head()
Out[225]:
YRSWRKPA_NORM ASISLEEP_NORM AHEIGHT_NORM BMI_NORM BEDDAYR_NORM CLCKTP_NORM AHCNOYR2_NORM LOCALL1B_NORM
0 0.800000 0.368421 0.117647 0.375267 0.000000 0.444444 0.250 0.500
1 0.371429 0.210526 0.588235 0.538913 0.010959 0.333333 0.000 0.875
2 0.371429 0.368421 0.176471 0.743870 0.016438 0.111111 0.375 0.625
3 0.457143 0.368421 0.235294 0.454424 0.000000 0.333333 0.250 1.000
4 0.628571 0.315789 0.176471 0.251866 0.000000 0.333333 0.250 0.250
In [226]:
health_cl_num_norm.dtypes
Out[226]:
YRSWRKPA_NORM    float64
ASISLEEP_NORM    float64
AHEIGHT_NORM     float64
BMI_NORM         float64
BEDDAYR_NORM     float64
CLCKTP_NORM      float64
AHCNOYR2_NORM    float64
LOCALL1B_NORM    float64
dtype: object
In [227]:
#Xcl = np.array(health_cl2.drop(['DBHVPAY_YES'], 1).astype(float64))
#Xcl = np.array(health_cl2.drop(['DBHVPAY_YES'], 1))
Xcl = np.array(health_cl_num_norm)
In [228]:
Xcl[0:5]
Out[228]:
array([[0.8 , 0.37, 0.12, 0.38, 0.  , 0.44, 0.25, 0.5 ],
       [0.37, 0.21, 0.59, 0.54, 0.01, 0.33, 0.  , 0.88],
       [0.37, 0.37, 0.18, 0.74, 0.02, 0.11, 0.38, 0.62],
       [0.46, 0.37, 0.24, 0.45, 0.  , 0.33, 0.25, 1.  ],
       [0.63, 0.32, 0.18, 0.25, 0.  , 0.33, 0.25, 0.25]])
In [231]:
#
kmeans = KMeans(n_clusters=5, max_iter=500, verbose = 0)
kmeans.fit(Xcl)
Out[231]:
KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=500,
    n_clusters=5, n_init=10, n_jobs=1, precompute_distances='auto',
    random_state=None, tol=0.0001, verbose=0)
In [233]:
#categorical dataset
health_cl1 = health_cl.iloc[:,0:135]
health_cl1.tail()
Out[233]:
DBHVPAY_YES SEX_2 R_MARITL_2 R_MARITL_3 R_MARITL_4 MRACRPI2_2 MRACRPI2_3 MRACRPI2_4 REGION_2 REGION_3 ... AWEBUSE_2.0 YTQU_YG1_2.0 ALCSTAT_2 ALCSTAT_3 ALCSTAT_5 ALCSTAT_6 ALCSTAT_7 ALCSTAT_8 ALCSTAT_9 ALCSTAT_10
15908 0 1 1 0 0 0 0 0 0 0 ... 0 1 0 0 0 1 0 0 0 0
15909 0 1 0 0 0 0 0 0 0 0 ... 0 1 0 0 0 0 1 0 0 0
15910 1 1 1 0 0 0 0 0 0 1 ... 0 1 0 0 0 0 1 0 0 0
15911 1 1 0 0 0 1 0 0 0 1 ... 0 1 0 0 1 0 0 0 0 0
15912 0 1 0 0 0 0 0 0 0 1 ... 0 1 0 0 0 1 0 0 0 0

5 rows × 135 columns

In [234]:
#merge 
health_cl2 = pd.concat([health_cl1,health_cl_num_norm],axis=1,join_axes=[health_cl1.index])
health_cl2.tail()
Out[234]:
DBHVPAY_YES SEX_2 R_MARITL_2 R_MARITL_3 R_MARITL_4 MRACRPI2_2 MRACRPI2_3 MRACRPI2_4 REGION_2 REGION_3 ... ALCSTAT_9 ALCSTAT_10 YRSWRKPA_NORM ASISLEEP_NORM AHEIGHT_NORM BMI_NORM BEDDAYR_NORM CLCKTP_NORM AHCNOYR2_NORM LOCALL1B_NORM
15908 0 1 1 0 0 0 0 0 0 0 ... 0 0 0.857143 0.315789 0.235294 0.123134 0.082192 0.333333 1.000 0.375
15909 0 1 0 0 0 0 0 0 0 0 ... 0 0 0.028571 0.368421 0.411765 0.140991 0.000000 0.333333 0.500 0.250
15910 1 1 1 0 0 0 0 0 0 1 ... 0 0 0.057143 0.368421 0.470588 0.554104 0.002740 0.333333 0.250 0.375
15911 1 1 0 0 0 1 0 0 0 1 ... 0 0 0.514286 0.315789 0.294118 0.600480 0.000000 0.333333 0.375 0.250
15912 0 1 0 0 0 0 0 0 0 1 ... 0 0 0.171429 0.368421 0.411765 0.089552 0.005479 0.444444 0.500 0.625

5 rows × 143 columns

In [235]:
#Xcl = np.array(health_cl2.drop(['DBHVPAY_YES'], 1).astype(float64))
#Xcl = np.array(health_cl2.drop(['DBHVPAY_YES'], 1))
Xcl = np.array(health_cl_num_norm)
In [236]:
Xcl[0:5]
Out[236]:
array([[0.8 , 0.37, 0.12, 0.38, 0.  , 0.44, 0.25, 0.5 ],
       [0.37, 0.21, 0.59, 0.54, 0.01, 0.33, 0.  , 0.88],
       [0.37, 0.37, 0.18, 0.74, 0.02, 0.11, 0.38, 0.62],
       [0.46, 0.37, 0.24, 0.45, 0.  , 0.33, 0.25, 1.  ],
       [0.63, 0.32, 0.18, 0.25, 0.  , 0.33, 0.25, 0.25]])
In [237]:
ycl = np.array(health_cl2['DBHVPAY_YES'])
In [238]:
ycl[0:5]
Out[238]:
array([1, 0, 1, 0, 0], dtype=uint8)
In [239]:
#
kmeans = KMeans(n_clusters=5, max_iter=500, verbose = 1)
kmeans.fit(Xcl)
Initialization complete
start iteration
done sorting
end inner loop
Iteration 0, inertia 3772.6783379936574
start iteration
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end inner loop
Iteration 1, inertia 3550.2887727135435
start iteration
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end inner loop
Iteration 2, inertia 3437.0332058683
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end inner loop
Iteration 3, inertia 3350.404469284882
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Iteration 4, inertia 3294.192427004905
start iteration
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end inner loop
Iteration 5, inertia 3264.3444804081423
start iteration
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end inner loop
Iteration 6, inertia 3249.883683426932
start iteration
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end inner loop
Iteration 7, inertia 3238.4031167018115
start iteration
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end inner loop
Iteration 8, inertia 3228.273151601613
start iteration
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end inner loop
Iteration 9, inertia 3218.164408140118
start iteration
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end inner loop
Iteration 10, inertia 3208.175158089976
start iteration
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Iteration 11, inertia 3196.5226195542623
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Iteration 12, inertia 3186.827065101367
start iteration
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Iteration 13, inertia 3179.380998873402
start iteration
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Iteration 14, inertia 3174.355297027626
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Iteration 15, inertia 3170.635486620739
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Iteration 16, inertia 3168.1929242151473
start iteration
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Iteration 17, inertia 3166.47150016391
start iteration
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end inner loop
Iteration 18, inertia 3165.582508451056
start iteration
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Iteration 19, inertia 3164.683146415009
start iteration
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end inner loop
Iteration 20, inertia 3164.0530584896464
start iteration
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end inner loop
Iteration 21, inertia 3163.6596337797055
start iteration
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end inner loop
Iteration 22, inertia 3163.4846834307764
start iteration
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end inner loop
Iteration 23, inertia 3163.4125671757215
start iteration
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end inner loop
Iteration 24, inertia 3163.374603676065
start iteration
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end inner loop
Iteration 25, inertia 3163.3570931671748
start iteration
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end inner loop
Iteration 26, inertia 3163.345328862697
start iteration
done sorting
end inner loop
Iteration 27, inertia 3163.3411025137507
center shift 1.706119e-03 within tolerance 4.675494e-06
Initialization complete
start iteration
done sorting
end inner loop
Iteration 0, inertia 3873.256326327427
start iteration
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end inner loop
Iteration 1, inertia 3608.7816655363918
start iteration
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end inner loop
Iteration 2, inertia 3551.874051719456
start iteration
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end inner loop
Iteration 3, inertia 3533.5351177730236
start iteration
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Iteration 4, inertia 3521.389565926247
start iteration
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end inner loop
Iteration 5, inertia 3507.9229646145254
start iteration
done sorting
end inner loop
Iteration 6, inertia 3494.317717450999
start iteration
done sorting
end inner loop
Iteration 7, inertia 3482.8683328168486
start iteration
done sorting
end inner loop
Iteration 8, inertia 3475.7032990764865
start iteration
done sorting
end inner loop
Iteration 9, inertia 3470.481685782549
start iteration
done sorting
end inner loop
Iteration 10, inertia 3464.0232997911307
start iteration
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end inner loop
Iteration 11, inertia 3451.9361836142075
start iteration
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end inner loop
Iteration 12, inertia 3424.283761140089
start iteration
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end inner loop
Iteration 13, inertia 3364.679549795684
start iteration
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end inner loop
Iteration 14, inertia 3286.2335853049394
start iteration
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end inner loop
Iteration 15, inertia 3246.6951731250188
start iteration
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end inner loop
Iteration 16, inertia 3236.6165167274703
start iteration
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end inner loop
Iteration 17, inertia 3233.550900399903
start iteration
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end inner loop
Iteration 18, inertia 3233.0503355454375
start iteration
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end inner loop
Iteration 19, inertia 3232.931674659189
start iteration
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end inner loop
Iteration 20, inertia 3232.9228758817753
start iteration
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end inner loop
Iteration 21, inertia 3232.920570937938
start iteration
done sorting
end inner loop
Iteration 22, inertia 3232.920570937938
center shift 0.000000e+00 within tolerance 4.675494e-06
Initialization complete
start iteration
done sorting
end inner loop
Iteration 0, inertia 3823.0534484848777
start iteration
done sorting
end inner loop
Iteration 1, inertia 3469.4930366511885
start iteration
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end inner loop
Iteration 2, inertia 3326.033895444982
start iteration
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end inner loop
Iteration 3, inertia 3239.997736595465
start iteration
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end inner loop
Iteration 4, inertia 3207.235436754204
start iteration
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end inner loop
Iteration 5, inertia 3186.395029253123
start iteration
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end inner loop
Iteration 6, inertia 3172.9205796173264
start iteration
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end inner loop
Iteration 7, inertia 3168.4480023817187
start iteration
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end inner loop
Iteration 8, inertia 3165.559057905397
start iteration
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end inner loop
Iteration 9, inertia 3164.2853855763656
start iteration
done sorting
end inner loop
Iteration 10, inertia 3163.853176453678
start iteration
done sorting
end inner loop
Iteration 11, inertia 3163.7072382298743
start iteration
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end inner loop
Iteration 12, inertia 3163.6087812881515
start iteration
done sorting
end inner loop
Iteration 13, inertia 3163.513502104757
start iteration
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end inner loop
Iteration 14, inertia 3163.446466616885
start iteration
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end inner loop
Iteration 15, inertia 3163.40200360988
start iteration
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end inner loop
Iteration 16, inertia 3163.3747688838707
start iteration
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end inner loop
Iteration 17, inertia 3163.3557205004063
start iteration
done sorting
end inner loop
Iteration 18, inertia 3163.3453827939716
start iteration
done sorting
end inner loop
Iteration 19, inertia 3163.339813208896
center shift 2.000169e-03 within tolerance 4.675494e-06
Initialization complete
start iteration
done sorting
end inner loop
Iteration 0, inertia 3702.9336796732955
start iteration
done sorting
end inner loop
Iteration 1, inertia 3469.645753480367
start iteration
done sorting
end inner loop
Iteration 2, inertia 3366.5195907330417
start iteration
done sorting
end inner loop
Iteration 3, inertia 3302.3643681120298
start iteration
done sorting
end inner loop
Iteration 4, inertia 3239.203347453182
start iteration
done sorting
end inner loop
Iteration 5, inertia 3169.4699530545386
start iteration
done sorting
end inner loop
Iteration 6, inertia 3130.0054504591735
start iteration
done sorting
end inner loop
Iteration 7, inertia 3118.628389563879
start iteration
done sorting
end inner loop
Iteration 8, inertia 3116.0822515788527
start iteration
done sorting
end inner loop
Iteration 9, inertia 3115.480981682948
start iteration
done sorting
end inner loop
Iteration 10, inertia 3115.2138466707197
start iteration
done sorting
end inner loop
Iteration 11, inertia 3115.0790634452496
start iteration
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end inner loop
Iteration 12, inertia 3114.997882200285
start iteration
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end inner loop
Iteration 13, inertia 3114.92759510232
start iteration
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end inner loop
Iteration 14, inertia 3114.862917153439
start iteration
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end inner loop
Iteration 15, inertia 3114.798334744491
start iteration
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end inner loop
Iteration 16, inertia 3114.7465839688657
start iteration
done sorting
end inner loop
Iteration 17, inertia 3114.684370738579
start iteration
done sorting
end inner loop
Iteration 18, inertia 3114.619633262393
start iteration
done sorting
end inner loop
Iteration 19, inertia 3114.5524076158927
start iteration
done sorting
end inner loop
Iteration 20, inertia 3114.4917291682805
start iteration
done sorting
end inner loop
Iteration 21, inertia 3114.4097736034882
start iteration
done sorting
end inner loop
Iteration 22, inertia 3114.2356248729066
start iteration
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end inner loop
Iteration 23, inertia 3113.905162838979
start iteration
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end inner loop
Iteration 24, inertia 3113.4215591041398
start iteration
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end inner loop
Iteration 25, inertia 3112.695225472834
start iteration
done sorting
end inner loop
Iteration 26, inertia 3112.134256504857
start iteration
done sorting
end inner loop
Iteration 27, inertia 3112.078825222901
start iteration
done sorting
end inner loop
Iteration 28, inertia 3112.071393742658
center shift 1.932050e-03 within tolerance 4.675494e-06
Initialization complete
start iteration
done sorting
end inner loop
Iteration 0, inertia 3609.3214467635153
start iteration
done sorting
end inner loop
Iteration 1, inertia 3333.1362833994463
start iteration
done sorting
end inner loop
Iteration 2, inertia 3265.0547612637006
start iteration
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end inner loop
Iteration 3, inertia 3234.3516894467853
start iteration
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end inner loop
Iteration 4, inertia 3209.867021647541
start iteration
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end inner loop
Iteration 5, inertia 3179.4107483621556
start iteration
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end inner loop
Iteration 6, inertia 3147.612661835856
start iteration
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end inner loop
Iteration 7, inertia 3130.767628576758
start iteration
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end inner loop
Iteration 8, inertia 3120.867206277381
start iteration
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end inner loop
Iteration 9, inertia 3118.4474904047042
start iteration
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end inner loop
Iteration 10, inertia 3117.7558433790273
start iteration
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end inner loop
Iteration 11, inertia 3117.4067000315717
start iteration
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end inner loop
Iteration 12, inertia 3117.1837296385725
start iteration
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end inner loop
Iteration 13, inertia 3116.925142292807
start iteration
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end inner loop
Iteration 14, inertia 3116.533757126223
start iteration
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end inner loop
Iteration 15, inertia 3115.7952938498047
start iteration
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end inner loop
Iteration 16, inertia 3114.7420314803558
start iteration
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end inner loop
Iteration 17, inertia 3113.4831002975325
start iteration
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end inner loop
Iteration 18, inertia 3112.3340597819906
start iteration
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end inner loop
Iteration 19, inertia 3112.0755863939567
start iteration
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end inner loop
Iteration 20, inertia 3112.067699941859
center shift 1.370791e-03 within tolerance 4.675494e-06
Initialization complete
start iteration
done sorting
end inner loop
Iteration 0, inertia 3774.9420644766096
start iteration
done sorting
end inner loop
Iteration 1, inertia 3420.7149275640113
start iteration
done sorting
end inner loop
Iteration 2, inertia 3300.8165084029883
start iteration
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end inner loop
Iteration 3, inertia 3259.349769424835
start iteration
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end inner loop
Iteration 4, inertia 3239.847643187288
start iteration
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end inner loop
Iteration 5, inertia 3226.579265603724
start iteration
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end inner loop
Iteration 6, inertia 3217.738619185436
start iteration
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end inner loop
Iteration 7, inertia 3206.072144719813
start iteration
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end inner loop
Iteration 8, inertia 3192.4495428121163
start iteration
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end inner loop
Iteration 9, inertia 3180.0206123284656
start iteration
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end inner loop
Iteration 10, inertia 3171.669149602481
start iteration
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end inner loop
Iteration 11, inertia 3167.0137400335097
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end inner loop
Iteration 12, inertia 3164.8165862299547
start iteration
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end inner loop
Iteration 13, inertia 3163.988093747741
start iteration
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end inner loop
Iteration 14, inertia 3163.6405000099235
start iteration
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end inner loop
Iteration 15, inertia 3163.508793254509
start iteration
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end inner loop
Iteration 16, inertia 3163.434455147254
start iteration
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end inner loop
Iteration 17, inertia 3163.3733932630216
start iteration
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end inner loop
Iteration 18, inertia 3163.3427769139594
start iteration
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end inner loop
Iteration 19, inertia 3163.3375868715634
center shift 1.685487e-03 within tolerance 4.675494e-06
Initialization complete
start iteration
done sorting
end inner loop
Iteration 0, inertia 3670.722821639735
start iteration
done sorting
end inner loop
Iteration 1, inertia 3463.463358224676
start iteration
done sorting
end inner loop
Iteration 2, inertia 3340.297907068545
start iteration
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end inner loop
Iteration 3, inertia 3275.2657985054752
start iteration
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end inner loop
Iteration 4, inertia 3238.1539037143807
start iteration
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end inner loop
Iteration 5, inertia 3206.2260461150145
start iteration
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end inner loop
Iteration 6, inertia 3186.0609271580656
start iteration
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end inner loop
Iteration 7, inertia 3175.6243817432696
start iteration
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end inner loop
Iteration 8, inertia 3170.3583014950523
start iteration
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end inner loop
Iteration 9, inertia 3166.994046387273
start iteration
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end inner loop
Iteration 10, inertia 3164.7654984173764
start iteration
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end inner loop
Iteration 11, inertia 3163.9106814183524
start iteration
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end inner loop
Iteration 12, inertia 3163.636243644627
start iteration
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end inner loop
Iteration 13, inertia 3163.502460969718
start iteration
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end inner loop
Iteration 14, inertia 3163.4217790801513
start iteration
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end inner loop
Iteration 15, inertia 3163.369275564348
start iteration
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end inner loop
Iteration 16, inertia 3163.3523293150715
start iteration
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end inner loop
Iteration 17, inertia 3163.347491241679
center shift 1.806771e-03 within tolerance 4.675494e-06
Initialization complete
start iteration
done sorting
end inner loop
Iteration 0, inertia 3690.607709449105
start iteration
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end inner loop
Iteration 1, inertia 3426.522103815754
start iteration
done sorting
end inner loop
Iteration 2, inertia 3301.8708005577782
start iteration
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end inner loop
Iteration 3, inertia 3247.2922248316336
start iteration
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end inner loop
Iteration 4, inertia 3233.4971996238946
start iteration
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end inner loop
Iteration 5, inertia 3228.317960082404
start iteration
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end inner loop
Iteration 6, inertia 3225.8213357047916
start iteration
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end inner loop
Iteration 7, inertia 3224.3284056341226
start iteration
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end inner loop
Iteration 8, inertia 3223.311973810425
start iteration
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end inner loop
Iteration 9, inertia 3222.7853150721035
start iteration
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end inner loop
Iteration 10, inertia 3222.524949241225
start iteration
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end inner loop
Iteration 11, inertia 3222.39142821217
start iteration
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end inner loop
Iteration 12, inertia 3222.2986365712795
start iteration
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end inner loop
Iteration 13, inertia 3222.2557034988263
start iteration
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end inner loop
Iteration 14, inertia 3222.228985364822
start iteration
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end inner loop
Iteration 15, inertia 3222.1910521351488
start iteration
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end inner loop
Iteration 16, inertia 3222.1733719127064
start iteration
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end inner loop
Iteration 17, inertia 3222.164082562402
start iteration
done sorting
end inner loop
Iteration 18, inertia 3222.157449882211
center shift 2.146962e-03 within tolerance 4.675494e-06
Initialization complete
start iteration
done sorting
end inner loop
Iteration 0, inertia 3734.9327203789676
start iteration
done sorting
end inner loop
Iteration 1, inertia 3349.178531694061
start iteration
done sorting
end inner loop
Iteration 2, inertia 3276.0518212639113
start iteration
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end inner loop
Iteration 3, inertia 3266.927025125481
start iteration
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end inner loop
Iteration 4, inertia 3263.348133360152
start iteration
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end inner loop
Iteration 5, inertia 3261.417426979671
start iteration
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end inner loop
Iteration 6, inertia 3260.467241930167
start iteration
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end inner loop
Iteration 7, inertia 3259.6818933630816
start iteration
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end inner loop
Iteration 8, inertia 3258.991923300212
start iteration
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end inner loop
Iteration 9, inertia 3258.416416319582
start iteration
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end inner loop
Iteration 10, inertia 3257.7803878180025
start iteration
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end inner loop
Iteration 11, inertia 3257.0850905801594
start iteration
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end inner loop
Iteration 12, inertia 3256.5179826091
start iteration
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end inner loop
Iteration 13, inertia 3255.8649651822325
start iteration
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end inner loop
Iteration 14, inertia 3255.1062999675514
start iteration
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end inner loop
Iteration 15, inertia 3253.962399946225
start iteration
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end inner loop
Iteration 16, inertia 3252.1244543676457
start iteration
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end inner loop
Iteration 17, inertia 3249.288003617488
start iteration
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end inner loop
Iteration 18, inertia 3245.3398675820554
start iteration
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end inner loop
Iteration 19, inertia 3239.6869150722328
start iteration
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end inner loop
Iteration 20, inertia 3233.9789534010974
start iteration
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end inner loop
Iteration 21, inertia 3218.5209910482495
start iteration
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end inner loop
Iteration 22, inertia 3183.5864101665334
start iteration
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end inner loop
Iteration 23, inertia 3146.6321645420267
start iteration
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end inner loop
Iteration 24, inertia 3128.676520238006
start iteration
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end inner loop
Iteration 25, inertia 3118.305847115342
start iteration
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end inner loop
Iteration 26, inertia 3113.608566079179
start iteration
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end inner loop
Iteration 27, inertia 3112.726632803999
start iteration
done sorting
end inner loop
Iteration 28, inertia 3112.4866327783648
start iteration
done sorting
end inner loop
Iteration 29, inertia 3112.356412994389
start iteration
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end inner loop
Iteration 30, inertia 3112.2664327257967
start iteration
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end inner loop
Iteration 31, inertia 3112.193698492989
start iteration
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end inner loop
Iteration 32, inertia 3112.161035466959
start iteration
done sorting
end inner loop
Iteration 33, inertia 3112.1539745937207
center shift 1.805806e-03 within tolerance 4.675494e-06
Initialization complete
start iteration
done sorting
end inner loop
Iteration 0, inertia 3449.171549727215
start iteration
done sorting
end inner loop
Iteration 1, inertia 3323.016291351783
start iteration
done sorting
end inner loop
Iteration 2, inertia 3284.2879778214865
start iteration
done sorting
end inner loop
Iteration 3, inertia 3264.2119350773937
start iteration
done sorting
end inner loop
Iteration 4, inertia 3254.8599120527174
start iteration
done sorting
end inner loop
Iteration 5, inertia 3251.342928431102
start iteration
done sorting
end inner loop
Iteration 6, inertia 3249.461284981595
start iteration
done sorting
end inner loop
Iteration 7, inertia 3248.4804401468227
start iteration
done sorting
end inner loop
Iteration 8, inertia 3247.2366173853684
start iteration
done sorting
end inner loop
Iteration 9, inertia 3245.763452503512
start iteration
done sorting
end inner loop
Iteration 10, inertia 3244.187534629102
start iteration
done sorting
end inner loop
Iteration 11, inertia 3242.814138406275
start iteration
done sorting
end inner loop
Iteration 12, inertia 3241.3078800564235
start iteration
done sorting
end inner loop
Iteration 13, inertia 3238.950338287244
start iteration
done sorting
end inner loop
Iteration 14, inertia 3235.606664523865
start iteration
done sorting
end inner loop
Iteration 15, inertia 3230.3411320874566
start iteration
done sorting
end inner loop
Iteration 16, inertia 3222.659007898148
start iteration
done sorting
end inner loop
Iteration 17, inertia 3214.067391012453
start iteration
done sorting
end inner loop
Iteration 18, inertia 3203.6947889284384
start iteration
done sorting
end inner loop
Iteration 19, inertia 3192.628352170656
start iteration
done sorting
end inner loop
Iteration 20, inertia 3183.3023944832967
start iteration
done sorting
end inner loop
Iteration 21, inertia 3176.993211089162
start iteration
done sorting
end inner loop
Iteration 22, inertia 3172.246370010851
start iteration
done sorting
end inner loop
Iteration 23, inertia 3169.2568020862473
start iteration
done sorting
end inner loop
Iteration 24, inertia 3167.2211337846384
start iteration
done sorting
end inner loop
Iteration 25, inertia 3165.9253678764517
start iteration
done sorting
end inner loop
Iteration 26, inertia 3165.0619958755783
start iteration
done sorting
end inner loop
Iteration 27, inertia 3164.275778659498
start iteration
done sorting
end inner loop
Iteration 28, inertia 3163.761151775765
start iteration
done sorting
end inner loop
Iteration 29, inertia 3163.523865824035
start iteration
done sorting
end inner loop
Iteration 30, inertia 3163.4299637876497
start iteration
done sorting
end inner loop
Iteration 31, inertia 3163.3835740556174
start iteration
done sorting
end inner loop
Iteration 32, inertia 3163.3624007131916
start iteration
done sorting
end inner loop
Iteration 33, inertia 3163.3481298509773
start iteration
done sorting
end inner loop
Iteration 34, inertia 3163.34322562274
center shift 1.824322e-03 within tolerance 4.675494e-06
Out[239]:
KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=500,
    n_clusters=5, n_init=10, n_jobs=1, precompute_distances='auto',
    random_state=None, tol=0.0001, verbose=1)
In [240]:
clusters = kmeans.predict(Xcl)
print clusters
[2 4 4 ... 0 2 4]
In [241]:
clusters.shape
Out[241]:
(15913L,)
In [242]:
ycl.shape
Out[242]:
(15913L,)
In [243]:
print completeness_score(ycl,clusters)
0.004936787674073858
In [244]:
print homogeneity_score(ycl,clusters)
0.011846832712906218
In [ ]:
#this clustering model cannot be used, it was an experiment for clustering numerical data with binary y variable.